Jobs / United States / Servicenow INC
Staff AI-Native DevOps Engineer
Servicenow INC · 🇺🇸 Santa Clara, CALIFORNIA, US
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 547 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 185 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Servicenow INC paid sponsored hires in similar roles1 certified filing for “Staff AI Implementation Engineer, AI Center of Excellence” (Software Developers) in TN: $141k–$141k, median $141k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Servicenow INC
The US Department of Labor certified 547 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 185 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Servicenow INC →
About the role
About the team The Conversational AI team at ServiceNow builds the core platform behind ServiceNow Otto, our conversational AI experience. We are a group of applied scientists and software engineers working at the intersection of research and production. Our work spans the full stack that makes Otto capable: agent orchestration, including harness engineering, prompt tuning, agent skills, policy design, and quality evaluation across languages; the A2A and MCP protocols that let agents collaborate and connect to tools; background channels and conversational triggers that bring agents into action; AI-native licensing and pricing; and the central caching layer that connects the ServiceNow platform to the services powering Otto. We are seeking a Staff AI-Native DevOps Engineer to join a new DevOps practice within the Conversational AI team. You will own the build, deployment, and reliability of the systems behind ServiceNow Otto, our conversational AI platform, from commit through production across our SaaS environments. Your work will span CI/CD pipelines, release automation, infrastructure on Kubernetes, observability, and the operational tooling that lets agent orchestration, MCP and A2A services, and the central caching layer ship safely and frequently. You will partner closely with applied scientists and software engineers to make AI-native delivery repeatable, measurable, and secure. This role combines deep expertise in cloud infrastructure, containerization, orchestration, and infrastructure as code with a practical understanding of how ML and LLM-based services behave in production, and a bias toward pragmatic engineering with measurable impact on deployment velocity and service reliability. To be successful in this role you have: • Deep expertise in designing, building, and operating scalable, reliable, and secure cloud-native applications and infrastructure. • Strong software engineering skills, with experience developing infrastructure tooling and automation using Go, Python, or similar languages. • Experience leading complex infrastructure initiatives, establishing engineering best practices, and driving adoption across multiple teams. • Strong problem-solving skills, with the ability to diagnose complex distributed systems issues and drive improvements in performance, reliability, and operational efficiency. • Strong understanding of modern AI technologies, including Large Language Models (LLMs), Generative AI, and agentic architectures, with the ability to apply these concepts to engineering and operational challenges. • An AI-native engineering mindset, proactively leveraging AI tools and automation to accelerate development, improve operational efficiency, and deliver more intelligent, resilient systems. DevOps: • Deploy, scale, and operate distributed microservices in production Kubernetes environments, including managing application lifecycle, networking, security, and service reliability. • Design and implement infrastructure automation using Infrastructure as Code (IaC) and Kubernetes-native tooling, including Terraform, Ansible, Helm, and Kubernetes Operators. • Build and maintain CI/CD pipelines and GitOps workflows using tools such as Jenkins, GitHub Actions, Tekton, and ArgoCD to automate testing, deployment, and release management. • Implement observability, monitoring, and incident response practices, performing root cause analysis and driving remediation to improve availability, fault tolerance, and operational resilience. • Architect and optimize cloud infrastructure across public and private cloud environments, with an emphasis on security, scalability, cost efficiency, and operational simplicity. AI skills: Artificial intelligence strategy is a critical skill at your level — it applies to ho