Embed & deploy agents by tackling problems alongside teams
Own deployments end-to-end: discovery, build, integration, activation, and tuning
Lead pilots and demos, drive adoption, and clear blockers
Build agentic systems with reasoning, planning, tool use, and coordination
Design safe tool-use infrastructure across APIs, databases, and services
Ship SDKs, patterns, and reusable blueprints for internal teams
Design and run rigorous evaluations to measure quality and catch regressions
Own multi-model inference for agents, focusing on latency and throughput
Set technical direction and standards for agentic systems; mentor engineers

5+ years in software engineering, with 3+ in AI systems or LLM applications, and production systems shipped end-to-end.
Strong grasp of LLM agent architectures (ReAct, RAG, tool use, multi-agent) and hands-on agentic orchestration and evaluation.
Proficiency in Python across a broad stack — pipeline, agent, service, and instrumentation.
Production experience on AWS and Azure with containerized deployments (Docker, Kubernetes).
Strong customer and stakeholder instincts; able to impose structure on ambiguity and push back when needed.
A bias toward shipping and comfort operating without a clean spec.
Solid understanding of agentic security risks (prompt injection, privilege escalation, data leakage).
Strong written and verbal communication.

Senior AI Engineer

Key skills