Software Engineer, AI Systems (United States)

What you'll do

• Build multi-step LLM pipelines and coordinate specialist agents, model calls, tools, graph queries, and retrieval.
• Design grounding and retrieval across graph traversal, vector search, and hybrid retrieval; develop evaluation datasets and regression suites.
• Operate production AI systems with tracing, audits, monitoring, failure handling, and quality dashboards, and help shape the AI roadmap.

What they ask for

• Experience shipping production AI or ML systems, including LLM systems used by real users.
• Hands-on experience building and debugging multi-step, tool-calling workflows with LangGraph, LangChain, or an equivalent framework; experience with repeatable LLM evaluation and retrieval for LLMs.
• Track record owning systems from deployment through monitoring and incident response; comfort working across model providers and explaining tradeoffs.
• Strong Python and production habits around FastAPI, asynchronous services, testing, observability, and maintainable interfaces.

Nice to have

• Comfort with Neo4j and Cypher or a comparable graph store; deep graph experience is strongly preferred.
• Experience with enterprise AI security, Azure and hybrid search platforms, or B2B Enterprise SaaS.

Tools

Neo4j, Cypher, LangGraph, LangChain, Python, FastAPI, OpenAI, Anthropic

AI focus

Build and operate multi-step LLM reasoning systems and coordinated agents for incident investigation, evidence retrieval, causal analysis, evaluation, and enterprise learning, with traceability and human oversight.