Careers at F7D8749A 72D6 407C Bf98 292Ea630C73A

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: As a Senior Systems Engineer on Shield AI’s next gen UAS program, you will play a pivotal role in designing, developing, and integrating cutting-edge autonomous aircraft systems for national defense. You will lead the technical execution of system architecture, ensuring seamless integration of avionics, autonomy, propulsion, sensor payloads, and mission-critical systems. This position requires a deep understanding of aerospace systems engineering, autonomy, and complex system integration. You will work cross-functionally with teams in hardware, software, autonomy, flight operations, and manufacturing to develop a scalable, mission-ready platform capable of operating in contested environments. Your expertise will be critical in defining system requirements and architectures through model-based systems engineering, conducting trade studies, ensuring compliance with military and aviation standards, and supporting the aircraft through flight testing and operational deployment. What You'll Do: Perform System Architecture & Design: Develop and refine the system architecture for the next gen UAS, ensuring seamless integration of avionics, autonomy, propulsion, sensor payloads, and mission systems. Define and document system-level behavior , including modes, states, transitions, and fault responses Support safety analyses (FHA, FMEA, FTA) by defining behavior under fault conditions Define and Manage System Requirements: Establish top-level requirements, decompose them into subsystems, and maintain traceability across the development lifecycle. Autonomy & AI Integration: Work closely with autonomy and software teams to integrate AI-driven flight control, decision-making, and mission execution capabilities. Model-Based Systems Engineering (MBSE): Utilize SysML, DOORS, or other MBSE tools to create digital system models, conduct trade studies, and optimize system performance. Risk Management & Trade Studies: Conduct trade studies to evaluate design alternatives, assess technical risks, and ensure the best engineering solutions for mission effectiveness. Stakeholder & Customer Engagement: Work closely with DoD stakeholders, industry partners, and government agencies to align system capabilities with operational requirements. Cross-Functional Collaboration: Partner with hardware, autonomy, software, propulsion, and flight operations teams to drive seamless system integration and rapid development cycles. Required Qualifications: 5+ years of experience in systems engineering for aerospace, defense, or autonomous aircraft systems. Demonstrated experience defining system behavior logic and operational modes Deep expertise in system architecture, avionics integration, and autonomy-driven flight systems. Proficiency in MBSE, DOORS, SysML, CAMEO, or similar system modeling tools for complex systems design and analysis. Experience with Group 4 or Group 5 UAS, military aircraft, or autonomous airborne platforms. Strong background in flight testing, system integration, and performance validation. Knowledge of DoD acquisition processes, MIL-STDs, FAA airworthiness certification, and airborne system safety standards. Demonstrated ability to lead cross-functional teams and drive complex projects to successful completion. Ability to work in a fast-paced, agile development environment with shifting priorities. Worked on developmental program from clean sheet to first flight Ability to obtain a S//SAR level security clearance desired. Preferred Qualifications: Experience developing AI-driven autonomy for unmanned aircraft. Expertise in ISR, EW, and advanced sensor integration for airborne platforms. Familiarity with modular open system architectures (MOSA) and Government Reference Architectures (GRA) for defense applications. Prior experience working with defense primes, DoD stakeholders, or government R&D programs. Active Secret or Top Secret clearance (or ability to obtain one). #LI-JM2 #LE Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Job Description: Join a high-impact software team focused entirely on delivering internal software tools to help other teams at Shield AI. The engineer in this role will help create, manage, deploy, and maintain new full-stack internal software tools. This role offers a unique opportunity to work with many different teams at Shield AI on a variety of different projects. Internal tools range from things as complex as physics analysis of the aircraft to things as simple as a system for tracking tickets. A successful engineer in this role would excel at gathering requirements for the tool, pushing back on bad requirements, and implementing a robust full-stack solution to deliver the best value to the team in need. This role offers high visibility projects that can change the workflows of entire teams for the better. What you'll do: Collaborate with other teams at Shield AI to hone tool requirements Architect a robust full-stack solution to meet the team's needs Deploy the tool internally for potentially wide reaching benefits Maintain an existing suite of internal tooling Required qualifications: Bachelor’s Degree in Computer Science Strong communication skills Familiarity with SQL Experience using frontend frameworks Experience using a compiled language Preferred qualifications: Experience making a full-stack web app React framework experience Rust language experience Microsoft SQL server experience Linux Proficiency #LI-AA1 #LA

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Join a high-impact software team focused entirely on delivering internal software tools to help other teams at Shield AI. The engineer in this role will help create, manage, deploy, and maintain new full-stack internal software tools. This role offers a unique opportunity to work with many different teams at Shield AI on a variety of different projects. Internal tools range from things as complex as physics analysis of the aircraft to things as simple as a system for tracking tickets. A successful engineer in this role would excel at gathering requirements for the tool, pushing back on bad requirements, and implementing a robust full-stack solution to deliver the best value to the team in need. This role offers high visibility projects that can change the workflows of entire teams for the better. What you'll do: Collaborate with other teams at Shield AI to hone tool requirements Architect a robust full-stack solution to meet the team's needs Deploy the tool internally for potentially wide reaching benefits Maintain an existing suite of internal tooling Required qualifications: Bachelor’s Degree in Computer Science Strong communication skills Linux Proficiency Strong low level performant language skills (C/C++ or Rust) Experience with SQL Experience using frontend frameworks Preferred qualifications: Experience making a full-stack web app Zero downtime deployment experience React framework experience Rust language experience Microsoft SQL server experience #LI-AA1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI is seeking a Staff Infrastructure Engineer to design, engineer, and support enterprise infrastructure across offices, engineering environments, data centers, and hybrid cloud platforms. As part of the Cloud & Infrastructure team within Enterprise Operations, this role will provide senior technical leadership across Active Directory, compute, virtualization, storage, backup and disaster recovery, and core infrastructure services. The Staff Infrastructure Engineer will remain hands-on while helping define scalable, secure, and resilient infrastructure standards that support Shield AI’s continued growth. This position is based in San Mateo, CA, or the surrounding San Francisco Bay Area, with regular on-site presence required. Occasional travel to other Shield AI offices, engineering sites, and data center locations may be required. What you'll do: Systems Engineering Serve as a senior technical resource on the Cloud & Infrastructure team, designing and implementing solutions for complex infrastructure requirements and technical challenges. Design, deploy, administer, and optimize Active Directory and core identity infrastructure, including domain services, Group Policy, DNS, authentication, replication, and integration with cloud identity services. Engineer and operate enterprise compute, virtualization, and storage infrastructure supporting business, engineering, and mission-critical workloads. Design, administer, and optimize enterprise storage platforms, including capacity planning, performance, availability, data protection, replication, and lifecycle management. Engineer and support compute platforms across data centers, colocation facilities, offices, and hybrid cloud environments, including virtualization, GPU-accelerated infrastructure, VDI, and specialized engineering workloads. Engineer and maintain Windows and Linux server infrastructure across Perform capacity planning and infrastructure sizing for new workloads, engineering environments, site expansions, and data center deployments. Design, deploy, and maintain data center and colocation infrastructure, including server and storage platforms, rack-level deployments, capacity planning, hardware lifecycle management, resiliency, and coordination with supporting teams and external providers. Perform infrastructure capacity planning and sizing for new workloads, engineering environments, site expansions, and data center deployments. Resiliency, Operations & Automation Design and continuously improve backup, disaster recovery, and infrastructure resiliency, including recovery architecture, replication, recovery objectives, testing, documentation, and execution of disaster recovery exercises. Implement monitoring and observability for infrastructure availability, capacity, performance, and reliability; identify and drive improvements before they become operational issues. Develop infrastructure automation and repeatable deployment patterns using Terraform, Ansible, PowerShell, Python, Bash, or similar technologies. Support integration between on-premises infrastructure and AWS/Azure, including workloads requiring hybrid connectivity or services, and support containerized or Kubernetes-based infrastructure where appropriate. Troubleshoot and resolve complex infrastructure incidents and serve as an escalation point for critical production issues. Participate in on-call, emergency response, and planned maintenance activities as required. Technical Leadership & Collaboration Partner with Cybersecurity on infrastructure hardening, vulnerability remediation, access controls, and compliance requirements. Partner with Network Engineering on infrastructure connectivity and dependency requirements while maintaining clear ownership boundaries for enterprise network architecture and network devices. Lead infrastructure projects and technical initiatives from design through implementation, including architecture, standards, operational documentation, and handoff procedures. Mentor engineers and provide technical guidance while remaining hands-on with infrastructure engineering and implementation. Develop and maintain infrastructure standards, architecture documentation, operational procedures, and engineering best practices. Required qualifications: Bachelor's degree in a technical discipline or equivalent practical experience. 8+ years of experience engineering and supporting enterprise infrastructure in production environments. Advanced experience administering and engineering Microsoft Active Directory, including AD DS, Group Policy, DNS, authentication, and replication. Strong experience with enterprise compute, virtualization, and storage platforms, including technologies such as VMware, Hyper-V, KVM, NetApp, Pure Storage, Dell EMC, or equivalent. Strong Windows Server administration experience and working proficiency with Linux systems such as RHEL or Ubuntu. Experience designing and implementing backup, replication, disaster recovery, and business continuity solutions, including RTO/RPO planning and testing. Experience with infrastructure automation and configuration management using tools such as Terraform, Ansible, PowerShell, Python, Bash, or similar technologies. Experience supporting hybrid infrastructure across on-premises environments and AWS and/or Azure. Demonstrated ability to lead complex technical initiatives, establish engineering standards, troubleshoot ambiguous problems, and mentor other engineers. Effective written and verbal communication skills, including the ability to communicate technical concepts to technical and non-technical audiences. Preferred qualifications: Experience supporting infrastructure in high-availability, mission-critical, manufacturing, aerospace, defense, or engineering environments. Deep experience with one or more enterprise storage and data protection ecosystems, including NetApp, Pure Storage, Dell EMC, or equivalent technologies. Experience designing infrastructure across multiple offices, engineering sites, laboratories, and data center or colocation environments. Experience with Kubernetes or containerized workloads and the underlying compute, storage, and infrastructure requirements that support them. Experience supporting GPU compute, high-performance computing, or other accelerated engineering workloads. Experience with VDI platforms such as VMware Horizon, Citrix, Azure Virtual Desktop, or equivalent technologies. Strong understanding of infrastructure networking fundamentals, including TCP/IP, DNS, DHCP, routing, VLANs, and firewalls. Experience operating in security-conscious or regulated environments and supporting infrastructure controls aligned with frameworks such as NIST or CMMC. Relevant technical certifications such as VMware VCP, Microsoft, NetApp, AWS, Azure, or equivalent certifications. #LI-KE1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . The Hivemind Software Engineering Integration and Test team is seeking a Staff Automated Test Engineer to provide technical leadership for automated verification across our next-generation autonomy platform. You will define and evolve test architecture, validation infrastructure, MLOps quality systems, and CI/CD pipelines that enable the Hivemind software ecosystem to create, test, and deploy resilient autonomy capabilities for unmanned aircraft and robotic platforms operating in complex, contested, and GPS-denied environments. You will work across production flight code, machine learning models, simulation and synthetic environments, mission planning and orchestration systems, operator-facing Ground Control Station applications, telemetry and data pipelines, cloud-native developer infrastructure, and hardware-in-the-loop systems. In this hands-on Staff role, you will lead complex, cross-functional initiatives, establish automation and verification standards, identify systemic quality risks, and develop scalable test infrastructure. The ideal candidate combines deep Python automation and distributed-systems testing experience with technical leadership and experience validating machine learning systems throughout the data, training, evaluation, deployment, and monitoring lifecycle. What you'll do: Own the technical strategy, architecture, and roadmap for automated testing, verification, and MLOps quality across the Hivemind ecosystem. Design and maintain scalable test frameworks for autonomy software, backend services, APIs, operator-facing applications, and distributed hardware environments. Lead functional, integration, regression, system, performance, reliability, and end-to-end testing across simulation, edge-compute, software-in-the-loop, and hardware-in-the-loop environments. Build automated ML validation pipelines covering data quality, training reproducibility, model accuracy, robustness, regression, latency, resource utilization, and system integration. Establish CI/CD and continuous training workflows that provide versioning and traceability for datasets, models, configurations, evaluation results, and deployment artifacts. Develop scenario-based validation for autonomy models, including edge cases, degraded sensing or communications, distribution shifts, and representative mission conditions. Create observability, analytics, and failure-triage capabilities for software behavior, model and data drift, inference health, test results, and production performance. Build Python automation that improves test execution, parallelization, reporting, environment setup, experiment comparison, and developer productivity. Create test harnesses, simulators, stubs, mocks, and synthetic data capabilities that improve system testability and coverage. Collaborate with software, autonomy, machine learning, data, simulation, and systems engineers to define verification strategies and improve designs before implementation. Develop and govern AI-assisted engineering workflows using coding agents and LLM-based tools for test generation, log analysis, debugging, and failure triage while maintaining security, reproducibility, and traceability. Required qualifications: Typically 8+ years of relevant experience in software engineering, test infrastructure, developer tooling, MLOps, systems integration, or systems verification, or an equivalent combination of experience and demonstrated impact. 5+ years of experience building scalable automation frameworks or developer tooling in Python. Demonstrated success designing test, CI/CD, or MLOps infrastructure used across multiple engineering teams. Experience validating machine learning systems across the data, training, evaluation, packaging, deployment, and monitoring lifecycle. Understanding of ML quality risks such as data leakage, training-serving skew, nondeterminism, distribution shift, drift, model regression, and statistical acceptance criteria. Experience defining model-performance baselines, automated evaluation suites, release thresholds, and candidate-to-production comparison workflows. Experience testing GPU-accelerated infrastructure and workloads, including GPU scheduling, allocation, utilization, and resource contention in Kubernetes environments. Experience with performance benchmarking, profiling, and observability for GPU workloads, including identifying compute, memory, storage, networking, and data-loading bottlenecks. Experience validating multi-tenant Kubernetes environments, including RBAC, resource quotas, workload isolation, and scheduling behavior. Experience qualifying integrated hardware and software systems, including automated validation of compute, GPU, storage, networking, drivers, firmware, and deployed software configurations. Strong system-design skills and experience testing distributed systems, backend services, APIs, and integrated hardware and software environments. Experience developing integration and regression strategies for internally developed, third-party, open-source, and partner software, including dependency management, compatibility testing, and upgrades. Strong understanding of asynchronous and concurrent Python programming for scalable automation and parallel test execution. Experience with package and dependency management, reproducible environments, and build systems such as Conan, pip, setuptools, Poetry, Nix, or similar. Experience with automated observability, log collection, analytics, reporting, and root-cause analysis in complex software, data, and infrastructure systems. Experience working in Linux-based development environments. Preferred qualifications: Experience with model registries, experiment tracking, dataset or feature versioning, model serving, and automated artifact promotion using MLflow, Kubeflow, Weights & Biases, SageMaker, Vertex AI, or similar platforms. Experience with GPU scheduling and orchestration platforms such as Run:ai, NVIDIA GPU Operator, KAI Scheduler, Kueue, Volcano, or similar technologies. Experience with NVIDIA GPU infrastructure, including CUDA, drivers, container runtimes, Multi-Instance GPU, GPU fractionalization, and hardware/software compatibility testing. Experience with GPU profiling and performance-analysis tools such as NVIDIA Nsight, PyTorch Profiler, or similar technologies. Experience validating perception, planning, decision-making, reinforcement learning, or other autonomy models in simulation and on deployed systems. Experience testing models on embedded or edge-compute platforms, including latency, memory, power, accelerator compatibility, quantization, and hardware-specific behavior. Experience qualifying production servers or appliances, including hardware validation, burn-in, provisioning, firmware, networking, storage, and software-stack validation before deployment. Experience with reliability, fault-injection, and recovery testing across distributed compute, storage, networking, and GPU infrastructure. Experience validating reproducible installation, operation, upgrades, and rollback in cloud, on-premises, disconnected, or air-gapped environments. Experience with containers, Kubernetes, cloud infrastructure, infrastructure as code, and reproducible test environments. Proficiency with Go or TypeScript for automation tooling or UI test development. Experience integrating Python with native C or C++ applications through bindings, wrappers, subprocess interfaces, or similar interoperability tooling. Aerospace, robotics, autonomy, embedded systems, or safety-critical software experience. Familiarity with software-in-the-loop, hardware-in-the-loop, requirements-based verification, configuration management, artifact traceability, or standards such as DO-178C and MIL-STD-882. #LI-DS5 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . The Hivemind Software Engineering Integration and Test team is seeking a Staff Automated Test Engineer to provide technical leadership for automated verification across our next-generation autonomy platform. You will define and evolve test architecture, validation infrastructure, MLOps quality systems, and CI/CD pipelines that enable the Hivemind software ecosystem to create, test, and deploy resilient autonomy capabilities for unmanned aircraft and robotic platforms operating in complex, contested, and GPS-denied environments. You will work across production flight code, machine learning models, simulation and synthetic environments, mission planning and orchestration systems, operator-facing Ground Control Station applications, telemetry and data pipelines, cloud-native developer infrastructure, and hardware-in-the-loop systems. In this hands-on Staff role, you will lead complex, cross-functional initiatives, establish automation and verification standards, identify systemic quality risks, and develop scalable test infrastructure. The ideal candidate combines deep Python automation and distributed-systems testing experience with technical leadership and experience validating machine learning systems throughout the data, training, evaluation, deployment, and monitoring lifecycle. What you'll do: Own the technical strategy, architecture, and roadmap for automated testing, verification, and MLOps quality across the Hivemind ecosystem. Design and maintain scalable test frameworks for autonomy software, backend services, APIs, operator-facing applications, and distributed hardware environments. Lead functional, integration, regression, system, performance, reliability, and end-to-end testing across simulation, edge-compute, software-in-the-loop, and hardware-in-the-loop environments. Build automated ML validation pipelines covering data quality, training reproducibility, model accuracy, robustness, regression, latency, resource utilization, and system integration. Establish CI/CD and continuous training workflows that provide versioning and traceability for datasets, models, configurations, evaluation results, and deployment artifacts. Develop scenario-based validation for autonomy models, including edge cases, degraded sensing or communications, distribution shifts, and representative mission conditions. Create observability, analytics, and failure-triage capabilities for software behavior, model and data drift, inference health, test results, and production performance. Build Python automation that improves test execution, parallelization, reporting, environment setup, experiment comparison, and developer productivity. Create test harnesses, simulators, stubs, mocks, and synthetic data capabilities that improve system testability and coverage. Collaborate with software, autonomy, machine learning, data, simulation, and systems engineers to define verification strategies and improve designs before implementation. Develop and govern AI-assisted engineering workflows using coding agents and LLM-based tools for test generation, log analysis, debugging, and failure triage while maintaining security, reproducibility, and traceability. Required qualifications: Typically 8+ years of relevant experience in software engineering, test infrastructure, developer tooling, MLOps, systems integration, or systems verification, or an equivalent combination of experience and demonstrated impact. 5+ years of experience building scalable automation frameworks or developer tooling in Python. Demonstrated success designing test, CI/CD, or MLOps infrastructure used across multiple engineering teams. Experience validating machine learning systems across the data, training, evaluation, packaging, deployment, and monitoring lifecycle. Understanding of ML quality risks such as data leakage, training-serving skew, nondeterminism, distribution shift, drift, model regression, and statistical acceptance criteria. Experience defining model-performance baselines, automated evaluation suites, release thresholds, and candidate-to-production comparison workflows. Experience testing GPU-accelerated infrastructure and workloads, including GPU scheduling, allocation, utilization, and resource contention in Kubernetes environments. Experience with performance benchmarking, profiling, and observability for GPU workloads, including identifying compute, memory, storage, networking, and data-loading bottlenecks. Experience validating multi-tenant Kubernetes environments, including RBAC, resource quotas, workload isolation, and scheduling behavior. Experience qualifying integrated hardware and software systems, including automated validation of compute, GPU, storage, networking, drivers, firmware, and deployed software configurations. Strong system-design skills and experience testing distributed systems, backend services, APIs, and integrated hardware and software environments. Experience developing integration and regression strategies for internally developed, third-party, open-source, and partner software, including dependency management, compatibility testing, and upgrades. Strong understanding of asynchronous and concurrent Python programming for scalable automation and parallel test execution. Experience with package and dependency management, reproducible environments, and build systems such as Conan, pip, setuptools, Poetry, Nix, or similar. Experience with automated observability, log collection, analytics, reporting, and root-cause analysis in complex software, data, and infrastructure systems. Experience working in Linux-based development environments. Preferred qualifications: Experience with model registries, experiment tracking, dataset or feature versioning, model serving, and automated artifact promotion using MLflow, Kubeflow, Weights & Biases, SageMaker, Vertex AI, or similar platforms. Experience with GPU scheduling and orchestration platforms such as Run:ai, NVIDIA GPU Operator, KAI Scheduler, Kueue, Volcano, or similar technologies. Experience with NVIDIA GPU infrastructure, including CUDA, drivers, container runtimes, Multi-Instance GPU, GPU fractionalization, and hardware/software compatibility testing. Experience with GPU profiling and performance-analysis tools such as NVIDIA Nsight, PyTorch Profiler, or similar technologies. Experience validating perception, planning, decision-making, reinforcement learning, or other autonomy models in simulation and on deployed systems. Experience testing models on embedded or edge-compute platforms, including latency, memory, power, accelerator compatibility, quantization, and hardware-specific behavior. Experience qualifying production servers or appliances, including hardware validation, burn-in, provisioning, firmware, networking, storage, and software-stack validation before deployment. Experience with reliability, fault-injection, and recovery testing across distributed compute, storage, networking, and GPU infrastructure. Experience validating reproducible installation, operation, upgrades, and rollback in cloud, on-premises, disconnected, or air-gapped environments. Experience with containers, Kubernetes, cloud infrastructure, infrastructure as code, and reproducible test environments. Proficiency with Go or TypeScript for automation tooling or UI test development. Experience integrating Python with native C or C++ applications through bindings, wrappers, subprocess interfaces, or similar interoperability tooling. Aerospace, robotics, autonomy, embedded systems, or safety-critical software experience. Familiarity with software-in-the-loop, hardware-in-the-loop, requirements-based verification, configuration management, artifact traceability, or standards such as DO-178C and MIL-STD-882. #LI-DS5 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Are you a passionate and innovative engineer looking to help develop state-of-the-art AI and robotics products? Are you eager to make a positive difference in the world? Do you want to work alongside mission-driven and values-focused teammates? Shield AI is just the place for you! The Hivemind Integration & Test team is committed to ensuring our autonomy platform delivers a seamless developer experience and enables customers to build world-class autonomous systems. We focus on integrating, validating, and continuously improving the Hivemind ecosystem—spanning autonomy behaviors, sensor processing, multi-agent coordination, ground-control systems, and embedded platforms. Our mission is to ensure that autonomy developers can efficiently build, test, and deploy autonomous applications that meet real-world mission objectives. In this role, you will lead a team responsible for integrating, validating, and scaling the Hivemind autonomy platform across simulation, hardware-in-the-loop, and operational environments. You will serve as both a technical leader and people manager—guiding engineers in the development of robust integration and test capabilities while remaining actively engaged in hands-on system integration, validation, and customer-focused workflows. As a power user of the Hivemind SDK, you will develop a deep understanding of its capabilities, identify gaps from a customer perspective, and drive improvements across the platform. You will partner closely with Engineering, Product, and Program teams to integrate new autonomy capabilities, evaluate feature completeness, and ensure customers can efficiently build, test, and deploy mission-ready autonomous systems. This position bridges technical leadership, engineering execution, and real-world autonomy applications—ensuring our platform empowers customers to build reliable, world-class autonomous systems. What you'll do: Mentor, and develop a team of engineers focused on software integration, system validation, and developer experience. Establish team priorities, drive execution, and foster a culture of technical excellence, ownership, and continuous improvement. Actively contribute to system integration, validation, and debugging activities and develop deep expertise in our autonomy stack. Guide the architecture and implementation of integration frameworks, deployment workflows, and configuration management tools that streamline validation across Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and flight environments. Review system logs, telemetry, and rosbag data to diagnose integration defects Lead cross-functional investigations, establish corrective actions, and create tooling that accelerates debugging and issue resolution. Ensure integrated capabilities meet product requirements and interface specifications. Required qualifications: Typically requires a minimum of 7 years of related experience with a bachelor’s degree in CS, Comp Eng, Robotics, or a related field; or 6 years and a master’s degree; or 4 years with a PhD. Proficiency in programming languages including Python or C++. Experience with autonomous systems or middleware. Demonstrated experience designing integration workflows, communicating system dependencies, and triaging and reporting integration defects across subsystem boundaries. Strong problem-solving skills and a proven track record of delivering high-quality software solutions. Excellent communication skills, capable of collaborating effectively across various teams and presenting to customers or technical leadership. Experience leading software integration engineers and owning integration roadmaps and release schedules Preferred qualifications: Demonstrated experience building complex systems with a strong understanding of software architecture and design principles. Experience with hardware or embedded systems. Expert knowledge of Python. Experience with ROS. Experience with white box testing Familiarity with networking, operating-systems, and radio communications. Experience supporting customer applications #LI-DS5 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Are you a passionate and innovative engineer looking to help develop state-of-the-art AI and robotics products? Are you eager to make a positive difference in the world? Do you want to work alongside mission-driven and values-focused teammates? Shield AI is just the place for you! The Hivemind Quality team is committed to ensuring our autonomy platform delivers a seamless developer experience and enables customers to build world-class autonomous systems. We focus on integrating, validating, and continuously improving the Hivemind ecosystem—spanning autonomy behaviors, sensor processing, multi-agent coordination, ground-control systems, and embedded platforms. Our mission is to ensure that autonomy developers can efficiently build, test, and deploy autonomous applications that meet real-world mission objectives. We are seeking an experienced Software Integration Engineer passionate about autonomy development. In this role, you will become a power user of the Hivemind SDK, deeply understanding its capabilities and identifying gaps from a customer perspective. You will develop and validate customer use cases, evaluate the ease of use for autonomy developers, and provide actionable feedback to Engineering and Product teams. You will play a critical role in integrating new autonomy capabilities into the platform, assessing feature completeness, and anticipating novel customer workflows and edge cases. This position bridges the gap between engineering development and real-world autonomy applications—ensuring our platform empowers customers to build reliable, mission-ready autonomous systems. What you'll do: Become a systems integration expert for autonomous robotics: Develop deep expertise in our AI-powered autonomy stack. Learn to configure, deploy, and integrate multi-agent systems across simulation, hardware-in-the-loop, and flight platforms. Understand the full system end-to-end—from sensor inputs to autonomous behaviors. Integrate new capabilities into the autonomy stack: Collaborate cross-functionally with development teams to bring autonomy algorithms, perception pipelines, middleware, and platform interfaces into the integrated product. Ensure seamless interoperability between components. Enable platform bring-up and validation: Lead the integration of autonomy software onto new robotic hardware platforms. Configure sensor drivers, communication interfaces, and platform adapters to enable full autonomy stack functionality on prototype and production vehicles. Develop integration tooling & infrastructure: Architect and implement integration frameworks, deployment scripts, and configuration management tools that streamline bringing new capabilities into Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and flight environments. Support cross-platform compatibility: Work with other integration engineers to ensure the autonomy stack operates reliably across all supported platforms, operating systems, and deployment configurations. Identify and resolve integration issues across system boundaries. Analyze system behavior and root-cause issues: Evaluate system logs, telemetry, and rosbag data to diagnose integration defects. Collaborate with developers to isolate issues to specific subsystems and drive resolution. Create analysis tooling to accelerate debugging. Optimize integration workflows and CI/CD: Partner with DevOps teams to streamline integration pipelines, reduce build-to-deploy cycle times, and ensure robust continuous integration of new features. Define integration checkpoints and criteria for release readiness. Validate system requirements and interface contracts: Work with engineers to ensure integrated capabilities meet product requirements and interface specifications. Assist in developing tooling to verify end-to-end system compliance and traceability. Required qualifications: Typically requires a minimum of 7 years of related experience with a bachelor’s degree in CS, Comp Eng, Robotics, or a related field; or 6 years and a master’s degree; or 4 years with a PhD. Proficiency in programming languages including Python or C++. Experience with autonomous systems or server applications or middleware. Demonstrated experience designing integration workflows, communicating system dependencies, and triaging and reporting integration defects across subsystem boundaries. Proficiency with simulation tools and hardware-in-the-loop (HIL) testing environments. Strong expertise with CI/CD pipelines. Strong problem-solving skills and a proven track record of delivering high-quality software solutions. Excellent communication skills, capable of collaborating effectively across various teams and presenting to customers or technical leadership. Preferred qualifications: Demonstrated experience building complex systems with a strong understanding of software architecture and design principles. Experience with hardware or embedded systems. Expert knowledge of Python. Experience with ROS. Experience with white box testing Familiarity with networking, operating-systems, and radio communications. Experience designing automated tooling for testing for GUI applications. Experience designing automated tooling for testing server applications. #LI-DS5 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . Job Description: Are you a passionate and innovative engineer looking to help develop state-of-the-art AI and robotics products? Are you eager to make a positive difference in the world? Do you want to work alongside mission-driven and values-focused teammates? Shield AI is just the place for you! The Hivemind Quality team is committed to ensuring our autonomy platform delivers a seamless developer experience and enables customers to build world-class autonomous systems. We focus on integrating, validating, and continuously improving the Hivemind ecosystem—spanning autonomy behaviors, sensor processing, multi-agent coordination, ground-control systems, and embedded platforms. Our mission is to ensure that autonomy developers can efficiently build, test, and deploy autonomous applications that meet real-world mission objectives. We are seeking an experienced Software Integration Engineer passionate about autonomy development. In this role, you will become a power user of the Hivemind SDK, deeply understanding its capabilities and identifying gaps from a customer perspective. You will develop and validate customer use cases, evaluate the ease of use for autonomy developers, and provide actionable feedback to Engineering and Product teams. You will play a critical role in integrating new autonomy capabilities into the platform, assessing feature completeness, and anticipating novel customer workflows and edge cases. This position bridges the gap between engineering development and real-world autonomy applications—ensuring our platform empowers customers to build reliable, mission-ready autonomous systems. What you'll do: Become a systems integration expert for autonomous robotics: Develop deep expertise in our AI-powered autonomy stack. Learn to configure, deploy, and integrate multi-agent systems across simulation, hardware-in-the-loop, and flight platforms. Understand the full system end-to-end—from sensor inputs to autonomous behaviors. Integrate new capabilities into the autonomy stack: Collaborate cross-functionally with development teams to bring autonomy algorithms, perception pipelines, middleware, and platform interfaces into the integrated product. Ensure seamless interoperability between components. Enable platform bring-up and validation: Lead the integration of autonomy software onto new robotic hardware platforms. Configure sensor drivers, communication interfaces, and platform adapters to enable full autonomy stack functionality on prototype and production vehicles. Develop integration tooling & infrastructure: Architect and implement integration frameworks, deployment scripts, and configuration management tools that streamline bringing new capabilities into Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and flight environments. Support cross-platform compatibility: Work with other integration engineers to ensure the autonomy stack operates reliably across all supported platforms, operating systems, and deployment configurations. Identify and resolve integration issues across system boundaries. Analyze system behavior and root-cause issues: Evaluate system logs, telemetry, and rosbag data to diagnose integration defects. Collaborate with developers to isolate issues to specific subsystems and drive resolution. Create analysis tooling to accelerate debugging. Optimize integration workflows and CI/CD: Partner with DevOps teams to streamline integration pipelines, reduce build-to-deploy cycle times, and ensure robust continuous integration of new features. Define integration checkpoints and criteria for release readiness. Validate system requirements and interface contracts: Work with engineers to ensure integrated capabilities meet product requirements and interface specifications. Assist in developing tooling to verify end-to-end system compliance and traceability. Required qualifications: Typically requires a minimum of 7 years of related experience with a bachelor’s degree in CS, Comp Eng, Robotics, or a related field; or 6 years and a master’s degree; or 4 years with a PhD. Proficiency in programming languages including Python or C++. Experience with autonomous systems or server applications or middleware. Demonstrated experience designing integration workflows, communicating system dependencies, and triaging and reporting integration defects across subsystem boundaries. Proficiency with simulation tools and hardware-in-the-loop (HIL) testing environments. Strong expertise with CI/CD pipelines. Strong problem-solving skills and a proven track record of delivering high-quality software solutions. Excellent communication skills, capable of collaborating effectively across various teams and presenting to customers or technical leadership. Preferred qualifications: Demonstrated experience building complex systems with a strong understanding of software architecture and design principles. Experience with hardware or embedded systems. Expert knowledge of Python. Experience with ROS. Experience with white box testing Familiarity with networking, operating-systems, and radio communications. Experience designing automated tooling for testing for GUI applications. Experience designing automated tooling for testing server applications. #LI-DS5 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai . Follow Shield AI on LinkedIn , X , Instagram , and YouTube . About Shield AI Shield AI is a defense technology company with the mission of protecting service members and civilians with intelligent systems. We build autonomy systems for air, maritime, space, and other platforms operating in complex and contested environments. Forge is the engineering platform used to build, integrate, test, and operate Hivemind capabilities. It connects autonomy developers with the applications, services, compute, data, and workflows they need to move from local development to deployed systems. The Role We are looking for a full-stack engineer with strong frontend expertise who enjoys building customer-facing products, developer tools, and AI-assisted workflows. Your primary focus will be designing and building intuitive, responsive applications in TypeScript and React, with backend development and service integration as needed to deliver complete workflows. You will partner with internal subject-matter experts to build Forge applications for simulation, synthetic data generation, test and evaluation, and autonomy performance. You will use shared platform components and design application extension points that let downstream teams specialize these workflows. Shield AI’s internal Hivemind Pilot developers and Hivemind Solutions groups are your primary design partners. You will work directly with them to understand requirements, evaluate solutions, and improve the user experience through real use. Your work will help engineers understand complex systems, accelerate the development of autonomy software, and deliver reliable systems faster. What you'll do: Design and build frontend experiences in TypeScript and React for autonomy development workflows such as simulation, synthetic data generation, and test and evaluation. Translate complex technical workflows into intuitive apps and workflows. Partner with Hivemind Pilot developers, Hivemind Solutions teams, product, and design to understand user needs and improve applications through feedback. Use Forge’s UI Platform to deliver consistent application experiences and drive improvements through collaborating on concrete requirements. Integrate domain APIs and services, building or extending backend capabilities as needed to complete application workflows. Design reusable application components and extension points that let other teams specialize workflows. Key outcomes: A successful engineer in this role will help deliver the following outcomes: Hivemind teams adopt Forge applications that make it easier to develop, integrate, test, and diagnose autonomy capabilities. Engineers can complete workflows across domain services through coherent application experiences, with clear progress, results, and paths to investigate failures. Applications behave reliably across supported local, cluster, edge, and air-gapped environments. Other teams can extend and specialize application workflows through documented APIs and extension points. Engineers and AI agents can use application capabilities with appropriate permissions, visibility, and user control. Required qualifications: Experience delivering and supporting production web applications, with substantial ownership of frontend architecture and user experience. Strong proficiency with TypeScript and React, including component design, state management, asynchronous data handling, routing, auth, and web architecture. Ability to translate complex technical workflows into intuitive interfaces in collaboration with users, subject-matter experts, and designers. Experience building responsive, accessible interfaces and diagnosing frontend performance issues with profiling. Experience integrating APIs and handling loading states, errors, long-running operations, and evolving service contracts. Ability to work across the stack, including reading, debugging, and extending backend services in Go, Python, or a comparable language. Experience testing UI components, application behavior, and complete user workflows. Sound judgment about when to use shared platform capabilities, contribute reusable improvements, or keep a solution specific to an application. Clear communication skills and the ability to collaborate across product, design, platform, and domain teams. Preferred qualifications: Experience in every area below is not expected. Relevant experience may include: Developer tools or technical applications for simulation, experimentation, test and evaluation, or deployment. Complex interactive interfaces such as scientific visualizations, workflow editors, large data tables, or live telemetry displays. Frontend performance optimization for large datasets, frequent updates, or computationally intensive views. Applications built on extensible platforms, including plugin systems, micro-frontends, Web Components, or VS Code extensions. Schema-driven API development using OpenAPI, JSON Schema, Protocol Buffers, or generated clients. Service and device integration using REST, gRPC, WebSockets, MQTT, DDS, MAVLink, or patterns such as pub/sub messaging and streaming telemetry. AI-assisted application workflows and agent-tool integrations using protocols such as Model Context Protocol. Familiarity with robotics, autonomy, simulation, or embedded systems, particularly integrating with underlying services, platforms, or devices. Why join us: Connect your work directly to the mission. The applications you build help engineers develop, validate, and deliver autonomy software at scale. Own the experience engineers use every day. Shape how users interact with complex autonomy systems, with primary ownership of frontend development and the ability to carry improvements through backend integration. Influence the platform through real applications. Turn workflow needs into shared workflow capabilities that benefit the broader Hivemind ecosystem. Build alongside engaged users. Partner directly with AI/ML/sim domain experts, learn how they work, and see the effect of your decisions. Shape AI-assisted engineering workflows. Build applications where engineers and agents can work with shared context and tools while preserving user control and accountability. #LI-DM2 #LC Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.