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About the team The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning. This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like. The role As a Senior Staff Engineer, you own the architecture of an security harness with novel exploitability engine end to end, and you’re accountable for the decisions that shape everything downstream. You set technical direction, make the hard calls defensible, and multiply the engineers around you. What you’ll own The end-to-end architecture of the exploitability engine—from evidence ingestion and entity resolution, through the attack-path probability core and choke-point ranking, to the validation loop that keeps predictions honest. The decisions that cascade through the system: calibrated probability versus ordinal rank, identity as a first-class graph edge, assume-breach seeding, and how the most critical assets are defined. These are model-shaping calls, not implementation details. The probabilistic ranking core: edge-traversal probability, guided path search with hop and likelihood limits, correlated-control-failure modeling, and honest uncertainty bands. The calibration and validation loop—canaries, purple-team and incident replay, calibration measured by zone and vector—that turns modeled weights into evidence rather than opinion. Make-or-break metrics as first-class engineering targets, starting with entity-resolution accuracy and calibration quality. The build-on strategy—extending the existing portfolio rather than rebuilding it, and knowing precisely what to reuse and what must be net-new. What you’ll do Lead zero-to-one work at production scale: turn an ambiguous, novel problem into a reliable system other teams build on, and set the bar where no precedent exists. Drive technical direction across architecture, design, and code reviews, and raise the engineering bar across the incubation. Mentor senior engineers and lead by influence, not title. Partner with product, security R&D, SecOps to turn customer problems into architecture, and translate that architecture into decisions leaders can act on. Establish AI safety, security, governance, and guardrails for agentic systems running in production. What you bring A track record of owning architecture across a large system or multiple teams, with deep experience operating production-quality software. Hands-on depth in both agentic and LLM systems and probabilistic or ML-driven scoring—graph modeling, calibration, search and optimization, or risk and probability engineering. Proven zero-to-one at scale: you’ve taken an ambiguous problem to a reliable production system that others depend on. The judgment to make consequential architecture decisions under uncertainty, and make them defensible to engineers and executives alike. Command of distributed systems, APIs, cloud-native development, and data or graph systems. Expert-level Python, and/or Java, Go, or TypeScript. Technical leadership and mentorship that moves teams through influence. Applied interest in security problems—attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response—is strongly preferred. Experience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf is a plus. Experience with AI evaluation, safety, governance, or policy guardrails is a plus. 10+ years of software engineering experience, including leading the design and delivery of complex production systems. Demonstrated experience as the technical owner or lead for a major system or across teams. Depth building AI/ML-powered production systems; probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus. Modern AI experience: LLMs, RAG, embeddings, vector search, agentic harness and workflows, model evaluation, or AI observability. Strong programming experience in Python and/or Java, Go, or a similar language. Cloud-native technologies, distributed systems, APIs, databases, and scalable architectures. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. Cybersecurity or security-product experience, or familiarity with modern security architectures and operations, is strongly preferred. For positions in this location, we offer a base pay of $201,300 - $352,300 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the team The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning. This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like. The role As a Senior Staff Engineer, you own the architecture of an security harness with novel exploitability engine end to end, and you’re accountable for the decisions that shape everything downstream. You set technical direction, make the hard calls defensible, and multiply the engineers around you. What you’ll own The end-to-end architecture of the exploitability engine—from evidence ingestion and entity resolution, through the attack-path probability core and choke-point ranking, to the validation loop that keeps predictions honest. The decisions that cascade through the system: calibrated probability versus ordinal rank, identity as a first-class graph edge, assume-breach seeding, and how the most critical assets are defined. These are model-shaping calls, not implementation details. The probabilistic ranking core: edge-traversal probability, guided path search with hop and likelihood limits, correlated-control-failure modeling, and honest uncertainty bands. The calibration and validation loop—canaries, purple-team and incident replay, calibration measured by zone and vector—that turns modeled weights into evidence rather than opinion. Make-or-break metrics as first-class engineering targets, starting with entity-resolution accuracy and calibration quality. The build-on strategy—extending the existing portfolio rather than rebuilding it, and knowing precisely what to reuse and what must be net-new. What you’ll do Lead zero-to-one work at production scale: turn an ambiguous, novel problem into a reliable system other teams build on, and set the bar where no precedent exists. Drive technical direction across architecture, design, and code reviews, and raise the engineering bar across the incubation. Mentor senior engineers and lead by influence, not title. Partner with product, security R&D, SecOps to turn customer problems into architecture, and translate that architecture into decisions leaders can act on. Establish AI safety, security, governance, and guardrails for agentic systems running in production. What you bring A track record of owning architecture across a large system or multiple teams, with deep experience operating production-quality software. Hands-on depth in both agentic and LLM systems and probabilistic or ML-driven scoring—graph modeling, calibration, search and optimization, or risk and probability engineering. Proven zero-to-one at scale: you’ve taken an ambiguous problem to a reliable production system that others depend on. The judgment to make consequential architecture decisions under uncertainty, and make them defensible to engineers and executives alike. Command of distributed systems, APIs, cloud-native development, and data or graph systems. Expert-level Python, and/or Java, Go, or TypeScript. Technical leadership and mentorship that moves teams through influence. Applied interest in security problems—attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response—is strongly preferred. Experience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf is a plus. Experience with AI evaluation, safety, governance, or policy guardrails is a plus. 10+ years of software engineering experience, including leading the design and delivery of complex production systems. Demonstrated experience as the technical owner or lead for a major system or across teams. Depth building AI/ML-powered production systems; probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus. Modern AI experience: LLMs, RAG, embeddings, vector search, agentic harness and workflows, model evaluation, or AI observability. Strong programming experience in Python and/or Java, Go, or a similar language. Cloud-native technologies, distributed systems, APIs, databases, and scalable architectures. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. Cybersecurity or security-product experience, or familiarity with modern security architectures and operations, is strongly preferred. For positions in this location, we offer a base pay of $201,300 - $352,300 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the team The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning. This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like. The role As a Principal ML Engineer, you set the technical vision for exploitability-based security across the portfolio—not just one engine. You define the hardest modeling problems worth solving, set the direction other staff and senior engineers build within, and represent the work to executives, customers, and the broader engineering organization. What you’ll own The technical vision and architecture for exploitability-driven security: where the engine goes next, and the class of problems it should solve beyond any single release. The hardest unsolved modeling problems—how calibrated attack-path probability holds up across environments, how identity and agent surfaces enter the model, and how ground truth feeds back into it. The engineering standards and architectural direction that multiple teams build within: scalability, reliability, and the scientific rigor of the scoring. The build-on strategy across the portfolio: what the engine reuses from existing products, what must be net-new, and why. What you’ll do Set technical direction across multiple teams without direct authority, and turn ambitious ideas into working, enterprise-grade products. Explore and apply emerging AI to cybersecurity in fundamentally new ways—not simply bolt AI onto existing products. Represent the team’s technology and innovation with executives, customers, partners, and the broader engineering organization. Mentor staff and senior engineers, and raise the overall engineering bar through coaching and technical leadership. Champion AI-native engineering practices, including extensive use of coding agents and autonomous development, testing, evaluation, and operational workflows. Set the direction for AI safety, security, governance, and guardrails for agentic systems running in production. What you bring Deep expertise in modern AI/ML with a track record of building production AI systems—LLMs, foundation models, agentic architectures, RAG, retrieval, and model evaluation—alongside probabilistic or ML-driven scoring. The ability to set a compelling technical vision and drive it across teams, then go deep into architecture and code. A proven record of turning ambitious, ambiguous ideas into products that scale to enterprise workloads. An innovator’s mindset—challenging conventional approaches and seizing the openings created by rapidly evolving AI. Command of distributed systems, APIs, cloud-native platforms, and data or graph systems. Expert-level Python and modern AI frameworks and infrastructure; experience with Java, Go, or similar languages is valuable. Executive-level communication: able to articulate a compelling technical vision to engineers, customers, and senior leadership. Applied depth in security problems—threat detection, vulnerability and exposure management, identity security, risk prioritization, or autonomous remediation—is strongly preferred. Extensive use of AI-native development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf across the software development lifecycle. 15+ years of software engineering experience, including significant technical and engineering leadership responsibility. Demonstrated experience designing and delivering AI/ML-powered products and platforms in production. Experience leading technical initiatives spanning multiple teams without direct authority. Demonstrated ability to design systems that scale to enterprise workloads. Hands-on experience with frontier LLMs, agent frameworks, retrieval and vector technologies, and model evaluation and observability; probabilistic modeling or graph analytics is a strong plus. Strong backend engineering experience with distributed systems, APIs, microservices, and cloud-native architectures. Extensive experience using AI-native development tools and coding agents as part of the software development lifecycle. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. Cybersecurity products, or deep familiarity with modern security architectures and security operations, is strongly preferred. For positions in this location, we offer a base pay of $240,100 - $420,200 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

Join us to build the next generation of cloud-native reliability, release, and test platforms that enable engineering excellence, developer productivity, and high-confidence ServiceNow releases through automation, observability, and AI-driven operations. What you will do in this role: Build and operate cloud-native engineering platforms for software validation, release qualification, and operational readiness. Design production-like release and test environments that improve release confidence and deployment readiness. Develop automated quality gates to assess release health, operational risk, and production readiness. Integrate automated testing, observability, reliability signals, and deployment intelligence into CI/CD pipelines. Build reusable test frameworks, self-service environments, test data, mock services, and developer productivity tooling. Advance shift-left engineering through automated validation, continuous verification, and quality gates. Automate failure detection, policy validation, deployment verification, security checks, and reliability assessments. Lead Kubernetes-based platform evolution for scalable test infrastructure, release automation, and developer self-service. Resolve recurring infrastructure issues through sustainable software, systems, and networking solutions. Partner with engineering teams on design reviews, architecture standards, and automation-first reliability practices. To be successful in this role you have: 12+ years of experience in software, systems, platform, or reliability engineering. Deep Kubernetes expertise across architecture, operations, networking, storage, security, autoscaling, and multi-cluster environments. Experience building and operating large-scale Kubernetes platforms for cloud-native, mission-critical services. Experience integrating Kubernetes with CI/CD, GitOps, automated testing, and deployment validation. Experience designing cloud-native platforms for ephemeral environments, release qualifications, and automated validation. Proven ability to lead engineering excellence across developer productivity, platform engineering, release confidence, and modernization. Experience with progressive delivery, including canary releases, feature flags, automated rollback, and deployment verification. Experience with chaos engineering, resilience validation, disaster recovery, and reliability assessments. Expertise designing, authoring, testing, and debugging code in a team setting using languages such as Python, Go, Java, or Ruby. Experience using AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, and operational automation. Strong coding, observability, SLO, and cross-team collaboration skills to improve reliability, performance, and engineering standards. Good to have: Expertise in observability and monitoring applications, services, and networks at scale. Experience with DevOps automation, CI/CD pipelines, and agile methodologies, including GitLab CI/CD or similar tools. Experience building enterprise-scale test automation frameworks such as Playwright, Selenium, Cypress, REST Assured, PyTest, JUnit/TestNG, or equivalent technologies. Experience with test orchestration, test impact analysis, flaky test detection, parallel execution, and intelligent regression testing. Experience with service virtualization, contract testing, synthetic testing, and test data management. Experience building engineering platforms that support developer self-service and release engineering. Experience with infrastructure configuration management tools such as Ansible. Expertise with Kubernetes ecosystem technologies such as Helm, Argo CD, Argo Workflows, Kustomize, Istio/Linkerd, Gateway API/Ingress, Prometheus, OpenTelemetry, and container runtimes. Experience implementing GitOps using Argo CD, Flux, or similar technologies. Experience operating Kubernetes across AWS (EKS), Azure (AKS), and Google Cloud (GKE). What you can expect from us: At ServiceNow, we make work better for everyone – including our own employees. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible for our employees. Win as a Team is part of our culture, and we aspire to wow our customers. We stay hungry and humble and focus on creating belonging. Sustainability, inclusivity, and diversity are key focus areas within our business framework so that we have transparency, equity, and accountability to deliver meaningful, measurable change. With our vision and dedication for a better future already underway. Join us on this journey! In addition to a competitive salary, supportive teams, and a real opportunity to progress in your career with a forward-thinking organisation, we provide resources to help you and your loved ones be well. From benefits plans and programs, to mental health resources that offer coaching and 24/7 support, to family support resources and parental leave programs – we want to help you take care of yourself and your loved ones. Below is a glimpse into even more of our offerings or click here for a full list : Along with holidays, we have company-wide designated global well-being days where everyone is off and can spend time doing what matters most. Good working culture to support the balance you need in both work and life. Parental leave programs. Childcare and caregiving benefits. A learning experience platform built using our own technology, to support your learning and development goals as well as a tuition reimbursement program. A global, cross-functional mentoring program. We also have team building activities, various employee belonging groups, volunteering, and community outreach programs. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the Cloud Hardware Engineering Team The Cloud Hardware Engineering Team works with some of the most innovative and advanced technologies in the business. We are a highly collaborative and inclusive team where individuals with strong technical aptitude, deep industry expertise, and a collaborative attitude have the opportunity to grow their professional careers and mentor peers as they work across the organization. We provide competitive compensation, generous benefits, and a professional, innovation-focused work atmosphere. About the role As a Sr Staff Cloud Architect, you will directly lead enterprise-scale cloud architecture initiatives that shape ServiceNow's infrastructure across private, sovereign, and public cloud environments. Your architectures will ensure optimal performance, security, and cost efficiency across our global cloud footprint. This is a critical role requiring deep expertise across multiple technical domains. You will serve as a force multiplier, leveraging specialized knowledge in public cloud offerings, database performance, Linux kernel tuning, and modern CPU architectures to solve complex problems affecting our entire customer base from high-value enterprise accounts to new cloud deployments. The solutions you architect will power ServiceNow's platform including large-scale application and database deployments to specialty services like customer analytics, fleet telemetry, and AI workloads. What you get to do in this role: Architect enterprise-scale solutions spanning private datacenters, sovereign cloud, and public cloud platforms (AWS, Azure, GCP). Evaluate and benchmark emerging technologies, services, and architectural patterns prior to production adoption. Drive hardware enhancements from original concept through final implementation across all system architectures and assess impact of design decisions on performance, security, and capacity. Evaluate and test new products, frequently prior to general availability. You will help automate evaluations, determine issues with designs, help identify root cause issues, and drive vendors internal and external to resolve issues. Work closely with engineering and infrastructure teams across the organization to understand the impacts of new software platform enhancements on the private and public cloud stack. Lead research and development efforts to identify emerging cloud, hardware, and software technologies, architectures, and designs with hands-on opportunities to benchmark, validate, and determine viability for future system designs. Serve as top-tier escalation for complex issues. Conduct cross-domain root cause analysis for complex infrastructure issues, coordinating investigations across database, OS, networking, and hardware layers. To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 12 years of related experience with a Bachelor's degree in Computer Information Systems (CIS), Management Information Systems (MIS), Computer Science (CS), Computer Engineering (CE), Electrical Engineering (EE), or related field; or 8 years and a Master's degree; or a PhD with 5 years experience; or equivalent experience. 10+ years evaluating, cost-modeling and implementing new datacenter technologies, including managing multi-vendor RFPs. 10+ years profiling and evaluating Linux and database performance. 7+ years hands-on with AWS, Azure, or GCP (compute, storage, networking, managed databases, cost optimization) 3+ years with Kubernetes and containerized infrastructure at production scale. Proven ability to lead complex transformation initiatives across multiple organization units. Thought leader and mentor with proven force-multiplier impact. Excellent communication and customer skills, conflict management, and interpersonal skills. Must be able to communicate at a level appropriate to the audience. For positions in this location, we offer a base pay of $190,900 - $334,100 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

What you get to do in this role: Design, build, and operate cloud-native engineering platforms for software validation, release validation, and production readiness Design and maintain production-like release and test ServiceNow environments that improve release confidence and deployment readiness. Build and integrate automated test pipelines, observability, reliability signals, deployment intelligence, and quality gates into CI/CD workflows. Develop automation solutions that improve engineering productivity, streamline operations, and reduce manual toil through shift-left engineering practices. Build reusable frameworks, self-service engineering environments, test data management, mock services, and developer productivity tooling. Design and enhance Kubernetes-based platforms supporting scalable test infrastructure, release automation, cloud-native workloads, and developer self-service. Implement automated validation for failure detection, deployment verification, policy enforcement, security checks, resilience testing, and operational health assessments. Resolve complex platforms, infrastructure, and networking challenges through software engineering, systems design, and automation. Partner closely with engineering teams to improve platform reliability, release quality, cloud-native adoption, and engineering best practices. Participate in architecture reviews, technical design discussions, and implementation of scalable, automation-first engineering solutions. Influence technical decisions through strong engineering execution, collaboration, and delivery of high-quality platform capabilities. Mentor engineers through technical guidance, code reviews, knowledge sharing, and engineering best practices. Foster a culture of reliability, automation, operational excellence, continuous improvement, and customer-focused engineering. Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 8+ years of experience in Site Reliability Engineering (SRE), DevOps, Platform Engineering, Software Engineering, or Infrastructure Engineering with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience. Hands-on experience with Kubernetes across cluster operations, networking, storage, security, autoscaling, and multi-cluster environments. Experience building and operating cloud-native platforms supporting scalable, highly available services. Experience integrating Kubernetes with CI/CD, GitOps, automated test pipelines, deployment validation, and cloud-native deployment workflows. Experience designing and implementing automation to improve developer productivity, release quality, and operational efficiency. Experience with progressive delivery practices, including canary deployments, feature flags, automated rollback, and deployment verification. Experience with chaos engineering, resilience testing, disaster recovery, and reliability validation. Strong software engineering skills with hands-on experience designing, developing, testing, and debugging applications using Python, Go, Java, or Ruby. Experience leveraging AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, or operational automation is a plus. Strong understanding of observability, monitoring, SLI/SLOs, incident management, and production operations for distributed systems. Demonstrated ability to solve complex technical problems, drive projects independently, and collaborate effectively across engineering teams. Thrives in fast-paced, ambiguous environments with a strong ownership mindset, bias for action, and a passion for continuous learning and automation. Low ego, intellectually curious, and an effective collaborator who enjoys partnering with globally distributed teams to deliver reliable engineering solutions. Good to have: Experience with observability and monitoring platforms for applications, services, and distributed systems at scale. Experience with DevOps automation, CI/CD pipelines, GitOps, and Agile development practices using tools such as GitLab CI/CD, Argo CD, or Flux. Experience building and maintaining enterprise-scale test automation frameworks using technologies such as Playwright, Selenium, Cypress, REST Assured, PyTest, JUnit/TestNG, or equivalent. Experience with test orchestration, intelligent regression testing, test impact analysis, flaky test detection, parallel execution, and test data management. Experience with service virtualization, contract testing, synthetic testing, and building developer self-service engineering platforms. Experience with Infrastructure as Code and configuration management tools such as Ansible, Terraform, or equivalent. Experience with the Kubernetes ecosystem, including Helm, Argo Workflows, Kustomize, Istio/Linkerd, Gateway API/Ingress, Prometheus, OpenTelemetry, and container runtime technologies. Experience operating Kubernetes platforms across public cloud providers, including AWS (EKS), Azure (AKS), and Google Cloud (GKE). Experience implementing progressive delivery practices, including canary deployments, feature flags, deployment verification, and automated rollback. Familiarity with AI-assisted engineering, intelligent testing, operational automation, or cloud-native engineering platforms. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

We are building AI-enabled product capabilities that improve through data, feedback, and real-world use. We need the production systems that make those capabilities dependable: repeatable delivery, measurable quality, controlled learning loops, and reliable operation at scale. We’re looking for a hands-on Staff Engineer who can move machine-learning models, agentic workflows, and self-learning approaches from promising prototypes into secure, observable, continuously deployable production systems. This role sits at the intersection of ML systems, platform engineering, and site reliability engineering. You will partner with ML, data, product, and infrastructure teams to create a paved path from experimentation to production—and take ownership of how those systems perform and evolve once deployed. What you’ll do Design and build the production path for the complete ML lifecycle: data and feature preparation, training, experiment tracking, evaluation, artifact and model management, serving, monitoring, feedback collection, and retraining. Build continuous-delivery workflows for models, prompts, agent workflows, data dependencies, and supporting services. Establish automated quality, safety, performance, and compatibility checks. Implement safe rollout patterns such as shadow traffic, canaries, progressive delivery, feature flags, versioned artifacts, automated rollback, and operational kill switches. Turn self-learning approaches into controlled production feedback loops. Build systems for collecting outcomes, validating feedback, maintaining lineage, triggering model refreshes, comparing candidates, and promoting changes under explicit guardrails. Define and operate SLIs, SLOs, alerts, and error budgets across infrastructure, data pipelines, inference services, model quality, and product behavior. Connect model analytics and product telemetry with traditional operational signals so teams can understand whether a problem originates in infrastructure, data, model behavior, or the surrounding product. Improve the scalability, availability, latency, and cost efficiency of distributed training, inference, and data-processing workloads. Own capacity planning and resource optimization, including GPU resources where applicable. Participate in production ownership across the service lifecycle: architecture reviews, deployment, on-call, incident response, blameless postmortems, and systemic remediation. Build self-service platforms and automation that reduce operational toil and shorten the time required for ML engineers and data scientists to reach production. Apply LLMs or agentic automation to evaluation, troubleshooting, and operational workflows where they produce reliable, measurable improvements. Establish practical standards for cloud infrastructure, Kubernetes, infrastructure as code, observability, security, and compliance. Provide technical leadership across ML, data, product, and platform teams, mentoring engineers and influencing architecture without relying on formal authority. To be successful in this role you have: A track record of Staff-level technical ownership, typically gained through 7+ years of experience in software engineering, platform engineering, SRE, production engineering, or ML infrastructure. Strong software-engineering skills in Python and at least one production systems language such as Go, Java, C++, or Rust. Experience designing, operating, and troubleshooting distributed production systems, including failure analysis, capacity planning, and performance optimization. Hands-on experience with cloud infrastructure, containers and Kubernetes, infrastructure as code, CI/CD, and modern observability. Practical understanding of the ML lifecycle—including training, evaluation, model deployment, serving, monitoring, versioning, and retraining—and the ability to collaborate effectively with applied ML engineers or researchers. Experience distinguishing service-health problems from data-quality or model-quality problems. Familiarity with SRE practices such as SLIs/SLOs, error budgets, sustainable on-call, incident management, and blameless postmortems. A strong automation and internal-customer mindset: you build platforms that are reliable, understandable, and pleasant for other engineers to use. Excellent technical judgment and communication skills, especially when navigating ambiguity and coordinating across teams during production incidents. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.

About the opportunity We are seeking a passionate Senior Software Engineer to play a critical role in designing, developing, and maintaining the cutting-edge technology that powers Veza. In this role, you will work closely with cross-functional teams to build robust, scalable, and secure solutions that meet the evolving needs of our customers. This is an exciting opportunity to make a significant impact in a high-growth startup and contribute to its continued success. You will: Design, develop, and maintain backend services, ensuring high performance, scalability, and reliability. Collaborate with product managers, other software engineers, UX Designers and security experts to build product features that meet business objectives and security standards. Implement logging, monitoring, and auditing capabilities to ensure visibility and compliance with regulatory requirements. Continuously optimize and improve the performance, security, and scalability of the platform through code reviews, testing, and refactoring. Stay current with industry trends and emerging technologies and leverage them to drive innovation and improve our platform. 5+ years of developer experience Strong experience in backend programming languages (e.g., Java, Go, C++, Rust, Python, or similar). Background in enterprise-grade distributed systems Strong understanding and experience with AI development tools A deep understanding of good software design principles combined with a practical mindset. Excellent problem-solving skills, ability to work independently and collaboratively in a fast-paced environment and deliver high-quality solutions efficiently. Strong communication and interpersonal skills Self-driven and hands-on developers who enjoy writing code, solving problems, and building systems—more doers than talkers. Proven experience in designing and implementing RESTful APIs and microservices architectures. Background in IGA industry is a big plus Solid understanding of database(e.g., relational db) and caching mechanisms Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.