Jobs / United States / Servicenow INC
Sr Staff AI Engineer - Veza
Servicenow INC · 🇺🇸 Santa Clara, CALIFORNIA, US (Remote) · Remote
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
The Access AI team is the customer-obsessed engineering group building the agentic AI and enterprise-scale harness platform that powers agents for Access Management across all Identity Security Products. We build AI as foundational platform infrastructure — prioritizing robustness, performance, safety, and real-world customer impact at scale. Types of problems you’ll get to work on You will architect, build, and operate production-grade agentic AI systems—autonomous agents that reason over enterprise data and execute mission-critical identity security actions at Fortune 500 scale. As a tier-one technical leader at the intersection of Agent research and large-scale backend systems, you will shape the architectural patterns, scalability guardrails, and strategic vision for autonomous enterprise security. Your core focus areas: • Agentic architecture. Design and ship multi-agent systems — orchestration, tool use, planning loops, memory, and failure recovery — that operate reliably in production, not in notebooks. • Enterprise-grounded reasoning. Build agents that leverage Access Graph, Access Reviews, and permission and risk data — to make decisions with context no frontier model has on its own. • Trust, safety, and governance. Own the guardrails: observability, human-in-the-loop controls, and compliance infrastructure that make autonomous systems safe to deploy at scale. • Retrieval and grounding. Work closely with our different product teams, platform and graph teams to ensure agents are grounded in accurate, low-latency retrieval — RAG pipelines, semantic search, re-ranking, and evaluation — as a critical dependency of agentic quality. • Model integration and evaluation. Integrate frontier models, evaluate trade-offs across cost, latency, and capability for production use cases. • Engineering leadership. Raise the technical bar through architecture decisions, code reviews, and coaching — particularly on agentic design patterns and production AI discipline. Qualifications To be successful in this role you have: • 8+ years of software engineering with strong fundamentals in data structures, algorithms, and distributed systems. • Hands-on depth designing, shipping, and operating agentic systems in production — multi-agent orchestration, tool calling, planning loops, memory, and failure recovery. Not prototypes. • Production-grade Python. Systems language (Go, Java, or C++) is a plus. • Working experience with frontier AI SDKs (Anthropic, Google, or OpenAI) — prompt engineering, structured outputs, and model evaluation in production settings. • Familiarity with RAG and retrieval patterns in production — vector stores, hybrid search, and retrieval evaluation metrics. • Track record of technical leadership: architecture ownership, code quality bar-raising, and mentoring engineers on production AI practices. Nice to Have • Deeper specialization in search and retrieval at scale or MLOps/model observability. • Published work or open-source contributions in agentic systems or retrieval. • Exposure to LLM fine-tuning or inference optimization in production. Why join us Intelligence is commoditizing. Context and execution are not. With over 30 billion access permissions under management, global enterprises in Fortune 500 trust Veza to manage privileged access monitoring, non-human identity security, access entitlement management, and next-generation identity governance, we are building the system that makes AI actually work inside the enterprise to secure Enterprises. Redefining Agentic Identity Governance: • Agentic Search: Provides natural language, context-aware discovery capabilities across complex permission graphs, enabling rapid identification of access risks and opportunities. • Agentic Access Rev