Note: The job is a remote job and is open to candidates in USA. ServiceNow's Veza is an identity security company building AI-native access management and governance solutions. The Senior Staff AI Engineer will architect, build, and operate production-grade agentic AI systems for enterprise identity security, while shaping technical strategy, scalability, safety, retrieval, model integration, and engineering practices.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- Equity (when applicable)
- Variable/incentive compensation
- Health plans, including flexible spending accounts
- A 401(k) Plan with company match
- ESPP
- Matching donations
- A flexible time away plan
- Family leave programs
- We approach our distributed world of work with flexibility and trust.
Company Overview
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