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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. About the Role We are looking for a hands-on SDET Technical Lead to establish and lead Release Integration Testing within Release & Feature Qualification for AI Inference Core. The Production Engine for Inference Core — turning integrated features into reliable production releases. You will define the quality strategy across the pre-release and release cycle, from feature and model integration through branch stability, release qualification, deployment, and post-release learning. You will work across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware to make release risk visible and actionable. This is a technical-leadership role, not a coordination-only position. You will design test architecture, lead difficult debugging and release decisions, mentor engineers, and write software and automation alongside the team. Release Integration Testing (RIT) is the bridge between feature qualification and release qualification. Feature teams retain ownership of feature design, feature-level qualification, and feature regression. Release Integration Testing owns inference-core integration strategy, inference-path readiness approval, integrated cross-stack validation, and first-pass rollout triage. What Makes This Role Distinct Dedicated Release Integration Testing ownership: Engage before feature qualification completes while keeping the boundary clear: feature teams own feature behavior and qualification; Release Integration Testing owns integration strategy, readiness approval, integrated validation, and first-pass rollout triage. Inference-path readiness gate: Require evidence across unit, simulation, benchmark, feature, and integration testing, with explicit coverage gaps before release entry. Cross-stack test strategy: Define risk-based E2E and regression coverage for features spanning components, organizations, software layers, infrastructure, and hardware. Branch and rollout leadership: Establish measurable health standards for master and release branches, and coordinate inference-impacting rollout across multiple product and release projects. Hands-on technical authority: Lead through code, test architecture, difficult debugging, quality metrics, and evidence-based release decisions. Team multiplier: Raise the technical bar, mentor engineers, and align feature, infrastructure, integration, qualification, and release teams. What You Will Do Define the Release Integration Testing strategy, engagement criteria, ownership boundaries, entry and exit criteria, coverage expectations, and escalation thresholds for AI Inference Core. Engage early on high-risk inference changes; identify dependencies and interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware. Own the inference-path readiness gate by reviewing unit, simulation, benchmark, feature-test, and integration evidence, documenting gaps, and approving integration readiness before release entry. Lead integrated inference E2E validation across features and the cloud-to-wafer stack; promote durable feature tests and add risk-based scenarios to release regression. Improve master and release-branch stability through actionable health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines. Lead first-pass regression and rollout triage, coordinate owners through resolution, drive RCA, place missing coverage at the correct layer, and plan rollout across multiple product and release projects. Partner with and mentor SDETs, feature teams, Integration, Core Infra, release owners, and deployment teams; between active engagements, advance automation efficiency, diagnostics, probes, and roadmap test planning. Minimum Skills & Qualifications Strong software-engineering fundamentals and programming ability in Python Go, or a similar language. Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration. Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software. Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution. Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics. Ability to influence and align multiple engineering teams without relying solely on organizational authority. Clear communication and sound judgment during high-pressure release situations, including the ability to explain technical risk to engineering and leadership audiences. Preferred Skills Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems. Experience with AI infrastructure, model deployment, LLMs, multimodal workloads, or large-scale compute clusters. Experience building test frameworks, distributed test systems, release pipelines, dashboards, or internal developer tooling. Experience with performance testing, profiling, observability, fault injection, reliability, or production failure analysis. Experience in a startup or similarly fast-moving, resource-constrained engineering environment. Track record of taking a quality or release capability from zero to one and scaling it across teams. Familiarity with containers, cluster orchestration, cloud infrastructure, CI/CD, or high-performance computing. What Success Looks Like Release readiness is based on explicit criteria and high-signal evidence rather than intuition. Fewer inference-path integration defects are first discovered in final release qualification or production. Cross-component risks are found earlier, debug cycles are shorter, and coverage ownership is explicit. Master and release-branch health is measurable, actionable, and steadily improving. Test automation and release infrastructure shorten feedback loops without sacrificing signal quality. Release metrics and reports drive clear decisions, ownership, and predictable feature rollout. Engineers across the organization are more effective because Release Integration Testing provides strong technical direction, tooling, and mentorship. Location This role requires in-office presence, at least three days per week. Fully remote work is not available. Office locations: Sunnyvale, CA or Toronto, ON. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Cerebras is seeking an exceptional PCB Layout Lead to own the physical implementation of complex, high-performance printed circuit boards for AI systems. This role will translate schematics and engineering requirements into production-ready layouts, optimizing signal integrity, power integrity, thermal performance, reliability, and manufacturability. Responsibilities Own multilayer PCB layout from initial component placement through fabrication and assembly release. Translate schematics, mechanical constraints, and electrical requirements into constraint-driven board designs using industry-standard PCB layout tools. Define and implement board stackups, controlled-impedance structures, routing rules, reference planes, return paths, and length- and phase-matching constraints. Place and route high-speed digital, high-current power, and sensitive analog circuits, including dense BGA fanout and differential interfaces. Apply signal-integrity and power-integrity best practices to minimize crosstalk, discontinuities, noise, voltage drop, and electromagnetic interference. Collaborate with electrical, SI/PI, mechanical, thermal, compliance, manufacturing, and test engineers to establish constraints and resolve layout issues. Work with fabrication and assembly partners to select materials, validate stackups and via structures, and improve yield, cost, and schedule. Perform design reviews and DFM, DFA, and DFT checks; generate and verify fabrication drawings, assembly drawings, drill data, Gerbers, ODB++, IPC-2581, and related release packages. Maintain component footprints, padstacks, design libraries, layout standards, and release documentation. Support prototype builds, board bring-up, failure analysis, and layout revisions through production. Minimum Qualifications Bachelor’s degree in electrical engineering, electronics engineering, or a related field, or equivalent practical experience. 10+ years of hands-on experience laying out complex, high-speed, multilayer printed circuit boards. Expertise with Cadence Allegro PCB Designer and Constraint Manager; experience with Altium Designer or equivalent tools is also relevant. Strong knowledge of component placement, controlled-impedance routing, differential pairs, length matching, return-path continuity, and power distribution. Experience with dense BGA escape routing, HDI structures, blind and buried vias, microvias, via-in-pad, and backdrilling. Working knowledge of signal integrity, power integrity, EMI/EMC, thermal design, creepage and clearance, and high-current routing. Experience applying IPC standards and fabrication, assembly, test, and manufacturability requirements. Ability to create and review complete PCB fabrication and assembly release packages. Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities. Excellent collaborative and interpersonal skills with multi-disciplined teams. Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc. Preferred Qualifications Experience designing large, high-layer-count boards for compute, networking, server, or AI accelerator systems. Experience routing high-speed interfaces such as DDR4/DDR5, PCIe Gen4/Gen5 or later, Ethernet, USB, and multi-gigabit SerDes. Experience with high-current, low-voltage power delivery, VRM placement, decoupling strategy, copper balancing, and thermal optimization. Experience developing Allegro SKILL, scripts, or automation that improves layout quality and release efficiency. Demonstrated success delivering first-pass functional boards and supporting products from prototype through volume production. Location: Remote. Sunnyvale, CA (Hybrid) is highly preferred. The base salary range for this position is $210,000 – $230,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Cerebras is seeking an exceptional PCB Layout Lead to own the physical implementation of complex, high-performance printed circuit boards for AI systems. This role will translate schematics and engineering requirements into production-ready layouts, optimizing signal integrity, power integrity, thermal performance, reliability, and manufacturability. Responsibilities Own multilayer PCB layout from initial component placement through fabrication and assembly release. Translate schematics, mechanical constraints, and electrical requirements into constraint-driven board designs using industry-standard PCB layout tools. Define and implement board stackups, controlled-impedance structures, routing rules, reference planes, return paths, and length- and phase-matching constraints. Place and route high-speed digital, high-current power, and sensitive analog circuits, including dense BGA fanout and differential interfaces. Apply signal-integrity and power-integrity best practices to minimize crosstalk, discontinuities, noise, voltage drop, and electromagnetic interference. Collaborate with electrical, SI/PI, mechanical, thermal, compliance, manufacturing, and test engineers to establish constraints and resolve layout issues. Work with fabrication and assembly partners to select materials, validate stackups and via structures, and improve yield, cost, and schedule. Perform design reviews and DFM, DFA, and DFT checks; generate and verify fabrication drawings, assembly drawings, drill data, Gerbers, ODB++, IPC-2581, and related release packages. Maintain component footprints, padstacks, design libraries, layout standards, and release documentation. Support prototype builds, board bring-up, failure analysis, and layout revisions through production. Minimum Qualifications Bachelor’s degree in electrical engineering, electronics engineering, or a related field, or equivalent practical experience. 10+ years of hands-on experience laying out complex, high-speed, multilayer printed circuit boards. Expertise with Cadence Allegro PCB Designer and Constraint Manager; experience with Altium Designer or equivalent tools is also relevant. Strong knowledge of component placement, controlled-impedance routing, differential pairs, length matching, return-path continuity, and power distribution. Experience with dense BGA escape routing, HDI structures, blind and buried vias, microvias, via-in-pad, and backdrilling. Working knowledge of signal integrity, power integrity, EMI/EMC, thermal design, creepage and clearance, and high-current routing. Experience applying IPC standards and fabrication, assembly, test, and manufacturability requirements. Ability to create and review complete PCB fabrication and assembly release packages. Ability to thrive in a fast-paced, dynamic environment and adapt to changing priorities. Excellent collaborative and interpersonal skills with multi-disciplined teams. Experience working on server hardware, AI accelerators, hardware accelerator, datacenter, AI Hardware, enterprise product, GPU, CPU, TPU, server platform etc. Preferred Qualifications Experience designing large, high-layer-count boards for compute, networking, server, or AI accelerator systems. Experience routing high-speed interfaces such as DDR4/DDR5, PCIe Gen4/Gen5 or later, Ethernet, USB, and multi-gigabit SerDes. Experience with high-current, low-voltage power delivery, VRM placement, decoupling strategy, copper balancing, and thermal optimization. Experience developing Allegro SKILL, scripts, or automation that improves layout quality and release efficiency. Demonstrated success delivering first-pass functional boards and supporting products from prototype through volume production. Location: Remote. Sunnyvale, CA (Hybrid) is highly preferred. The base salary range for this position is $210,000 – $230,000+ annually. Actual compensation may include bonus and equity, and will be determined based on factors such as experience, skills, and qualifications. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. We are looking for an Application Security Engineer with a strong focus on Vulnerability Management to help secure Cerebras software, infrastructure, and AI platforms. You will own and evolve key parts of our vulnerability management program from vulnerability discovery and risk prioritization through remediation and verification. This is not a ticket-management role. We are looking for an engineer who can understand vulnerabilities in context, work directly with engineering teams, automate repetitive security work, and help eliminate classes of vulnerabilities rather than simply track individual findings. You will work closely with Engineering, Infrastructure, and IT teams to identify vulnerabilities across our products and environments and drive them to meaningful remediation. Responsibilities Own and continuously improve vulnerability management across applications, software dependencies, containers, operating systems, cloud infrastructure, and externally exposed services. Use AI agents and advanced security models to augment vulnerability discovery, code analysis, adversarial testing, prioritization, and remediation. Analyze vulnerabilities beyond scanner severity by considering exploitability, exposure, affected assets, available mitigations, and business impact. Partner directly with engineering teams to triage findings, determine appropriate remediation, and drive vulnerabilities to closure within risk-based SLAs. Build automation for vulnerability ingestion, deduplication, enrichment, prioritization, assignment, remediation tracking, and reporting. Identify systemic vulnerability patterns and work with engineering teams to address root causes rather than repeatedly fixing individual findings. Operate and improve application security capabilities including SAST, SCA, secrets detection, container scanning, infrastructure scanning, and external attack-surface monitoring. Validate security findings through technical investigation and hands-on testing, distinguishing exploitable vulnerabilities from false positives and low-risk findings. Perform targeted application security reviews and testing for high-risk services and features. Help integrate security controls into CI/CD and developer workflows while minimizing unnecessary friction for engineering teams. Develop metrics and reporting that provide meaningful visibility into vulnerability exposure, remediation performance, recurring vulnerability classes, and security risk. Evaluate and integrate new security technologies as our software and infrastructure environments evolve. Partner with security and engineering teams on incident response when vulnerabilities are actively exploited or require urgent remediation. Skills & Qualifications We are looking for candidates who: Have strong application security or product security fundamentals and hands-on experience with vulnerability management. Understand common vulnerability classes and exploitation techniques across web applications, APIs, authentication systems, cloud services, containers, and software supply chains. Can read and reason about code and work effectively with software engineers on practical remediation. Have experience with vulnerability scanning and application security technologies such as SAST, SCA, DAST, secrets scanning, container scanning, or CSPM. Understand vulnerability prioritization concepts including CVSS, exploitability, asset criticality, internet exposure, compensating controls, and threat intelligence. Are comfortable investigating security findings manually rather than relying exclusively on scanner output. Can automate security workflows using languages such as Python, Go, or similar scripting/programming languages. Have experience integrating security tooling into CI/CD and modern software development workflows. Are comfortable working with Linux, Git, containers, and cloud environments. Can communicate security risk clearly to both security specialists and engineering teams. Approach security with an automation-first mindset and look for scalable solutions instead of manual processes. Preferred Qualifications Experience in one or more of the following areas is a plus: Application Security or Security engineering background. Securing AI/ML platforms, inference services, or large-scale compute infrastructure. Building or operating vulnerability management programs at scale. AWS, Kubernetes, Docker, and cloud-native environments. Software supply-chain security and dependency management. GitHub and CI/CD security. Threat modeling and secure design reviews. Penetration testing or offensive security. External attack-surface management. Vulnerability research or exploit validation. Security data pipelines, APIs, and workflow automation. Using LLMs, AI agents, or AI-assisted security tooling for vulnerability research, code analysis, penetration testing, or remediation. What Success Looks Like You will help Cerebras move beyond simply finding vulnerabilities toward an engineering-driven vulnerability management program where: The vulnerabilities that create the most meaningful risk are identified and prioritized quickly. Engineering teams receive actionable findings with clear remediation guidance. High-risk vulnerabilities are consistently remediated within defined SLAs. Security findings are increasingly validated, prioritized, and routed automatically. Recurring vulnerability classes are addressed systematically. AI and automation reduce manual security work and accelerate both vulnerability discovery and remediation. Most importantly, you will help build security processes that scale with the speed at which Cerebras builds and deploys some of the most advanced AI systems in the world.ADD DESCRIPTION HERE Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Responsibilities: Drive the design and architecture of secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers. Design and implement IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM. Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go. Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization. Partner across Security, Engineering, and Infrastructure teams to drive secure-by-design solutions, implement Zero Trust principles, and reduce operational friction. Drive technical direction and cross-team initiatives that improve the scalability, reliability, security, and developer experience of our infrastructure. Write high-quality, reliable code, participate in architecture and code reviews, mentor engineers, and help raise the technical bar across the team. Support critical production systems and drive operational excellence through scalability, resiliency, observability, and automation. Participate in on-call and incident response for the Developer Productivity organization. Skills & Qualifications 7+ years of experience in Cloud Infrastructure, Platform Engineering, Identity & Access Management, Identity Engineering, or Security Engineering. Proven experience designing and owning complex production infrastructure or platform systems at scale. Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC. Experience designing and operating identity and access controls within AWS environments, with hands-on experience building and operating production-level services on AWS. Experience working with container technologies and deploying and operating services on Kubernetes. Strong automation and coding skills with Python or Go, along with Terraform or similar IaC technologies. A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR. A strong platform and operational mindset, with experience supporting and improving production services through monitoring, troubleshooting, incident response, and automation. Demonstrated ability to influence technical direction, drive cross-team initiatives, and mentor other engineers. Excellent collaboration and communication skills, with a proven ability to work across teams and influence technical decisions. Preferred Skills & Qualifications Hands-on experience with identity platforms such as Okta, Microsoft Entra ID (Azure AD), or modern IAM/IGA platforms. Experience with Azure and/or GCP is a bonus. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Responsibilities: Drive the design and architecture of secure, scalable cloud infrastructure and identity platforms in AWS and our own data centers. Design and implement IAM, IGA, authentication, authorization, SSO, MFA, identity lifecycle management, and provisioning/deprovisioning solutions using modern identity platforms and standards such as SAML, OAuth2, OIDC, and SCIM. Develop automation, integrations, and infrastructure-as-code solutions using Terraform and programming languages such as Python and Go. Design and implement security controls for AI-powered systems, including controlled, audited, and governed agent workflows, while contributing to core security services such as service identity, secrets management, key management, authentication, and authorization. Partner across Security, Engineering, and Infrastructure teams to drive secure-by-design solutions, implement Zero Trust principles, and reduce operational friction. Drive technical direction and cross-team initiatives that improve the scalability, reliability, security, and developer experience of our infrastructure. Write high-quality, reliable code, participate in architecture and code reviews, mentor engineers, and help raise the technical bar across the team. Support critical production systems and drive operational excellence through scalability, resiliency, observability, and automation. Participate in on-call and incident response for the Developer Productivity organization. Skills & Qualifications 7+ years of experience in Cloud Infrastructure, Platform Engineering, Identity & Access Management, Identity Engineering, or Security Engineering. Proven experience designing and owning complex production infrastructure or platform systems at scale. Strong knowledge of authentication, authorization, identity lifecycle management, and federation protocols including SAML, OAuth2, OIDC, SCIM, and RBAC. Experience designing and operating identity and access controls within AWS environments, with hands-on experience building and operating production-level services on AWS. Experience working with container technologies and deploying and operating services on Kubernetes. Strong automation and coding skills with Python or Go, along with Terraform or similar IaC technologies. A security-first mindset with experience implementing Zero Trust, least-privilege access, and compliance frameworks such as SOC2, FedRAMP, or ITAR. A strong platform and operational mindset, with experience supporting and improving production services through monitoring, troubleshooting, incident response, and automation. Demonstrated ability to influence technical direction, drive cross-team initiatives, and mentor other engineers. Excellent collaboration and communication skills, with a proven ability to work across teams and influence technical decisions. Preferred Skills & Qualifications Hands-on experience with identity platforms such as Okta, Microsoft Entra ID (Azure AD), or modern IAM/IGA platforms. Experience with Azure and/or GCP is a bonus. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Responsibilities: Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization. Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale. Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes. Provision, monitor, and optimize cloud infrastructure supporting CI workloads, balancing cost, performance, scalability, and reliability. Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes. Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity. Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure. Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows. Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization. Participate in on-call and incident response for Developer Productivity systems and services. Skills & Qualifications 7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area. Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure. Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts. Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning. Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management. Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation. Experience with containerization and container orchestration, with Kubernetes preferred. Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues. Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale. Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues. Experience operating production systems and participating in on-call, incident response, and postmortem processes. Preferred Skills & Qualifications Experience with infrastructure-as-code tools and practices. Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling. Experience with build systems, build graph optimization, or large-scale build infrastructure. Experience with observability practices including monitoring, logging, alerting, and performance analysis. Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure. Experience applying AI/LLM tooling to engineering workflows or developer productivity. BS/MS in Computer Science or a related field, or equivalent practical experience. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Responsibilities: Design, build, and evolve CI/CD pipelines that support reliable and efficient build, test, and release workflows across the organization. Own and improve artifact lifecycle systems, including versioning, storage, distribution, dependency management, and reproducible builds at scale. Partner with development teams to design and improve code review workflows, branching strategies, and automated integration processes. Provision, monitor, and optimize cloud infrastructure supporting CI workloads, balancing cost, performance, scalability, and reliability. Troubleshoot complex build failures, pipeline bottlenecks, and infrastructure issues, driving root-cause analysis and implementing durable fixes. Design and drive improvements to internal build infrastructure, test infrastructure, developer tooling, and automation that increase developer velocity and engineering productivity. Identify systemic bottlenecks across developer workflows and lead architectural improvements to developer infrastructure. Contribute to the company’s efforts around AI tooling to improve engineering productivity and automate repetitive workflows. Provide technical leadership across projects, influence engineering standards, and mentor other engineers within the Developer Productivity organization. Participate in on-call and incident response for Developer Productivity systems and services. Skills & Qualifications 7+ years of professional experience in software engineering, infrastructure engineering, DevOps, developer productivity, or a related area. Deep hands-on experience with CI/CD systems and building or evolving automated build, test, and deployment infrastructure. Experience with artifact repositories, software packaging, dependency management, and reproducible build concepts. Experience with cloud computing platforms, with AWS preferred, and programmatic infrastructure provisioning. Strong experience with distributed version control systems, code review workflows, branching strategies, and repository management. Strong understanding of Linux/Unix systems, networking fundamentals, and scripting or programming for automation. Experience with containerization and container orchestration, with Kubernetes preferred. Strong troubleshooting skills and the ability to debug complex distributed systems and infrastructure issues. Demonstrated experience leading technical initiatives across multiple teams and driving improvements to developer infrastructure at organizational scale. Ability to identify architectural bottlenecks, evaluate tradeoffs, and drive long-term improvements rather than only addressing operational issues. Experience operating production systems and participating in on-call, incident response, and postmortem processes. Preferred Skills & Qualifications Experience with infrastructure-as-code tools and practices. Proficiency in Python, Go, Shell, or another language used for infrastructure automation and developer tooling. Experience with build systems, build graph optimization, or large-scale build infrastructure. Experience with observability practices including monitoring, logging, alerting, and performance analysis. Experience building internal developer platforms, self-service tooling, or developer-facing infrastructure. Experience applying AI/LLM tooling to engineering workflows or developer productivity. BS/MS in Computer Science or a related field, or equivalent practical experience. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras here ! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.