Artificial Intelligence Engineer

AI Engineer

Our client, is looking for an AI Engineer to own and evolve a production conversational AI system. This assistant lets users ask natural-language questions and get back formatted answers, charts, and tables — powered by a LangGraph tool-calling agent, guardrails, and retrieval-augmented generation at scale.

What You'll Do

• Extend the core chat pipeline: guardrails, query reformulation, embedding-based tool routing, agent orchestration, and response formatting


• Maintain and grow a large domain tool layer over an internal API (schemas, auth checks, pagination, error handling)


• Support a live production system: triage incidents, investigate latency/quality regressions, improve telemetry and runbooks


• Improve RAG retrieval quality using PostgreSQL full-text search and pgvector, including hybrid approaches


• Build evaluation practices that gate model/prompt changes: adversarial datasets, tool-selection accuracy, shadow traffic, canary rollouts, auto-rollback


• Reduce LLM cost/latency via token telemetry, prompt trimming, caching, and model tiering


• Strengthen security: tenant-scoped data access, server-side authorization, and prompt-injection defenses


• Expand automated testing across commit, PR, nightly, and release gates

Must-Haves

• 3+ years building production backend services, including at least one shipped LLM-backed feature


• Proven ability to take ownership of unfamiliar codebases safely using tests and traces


• Strong async Python with strict typing discipline (mypy)


• Hands-on experience with LangChain, LangGraph, or similar agent frameworks (tool/function calling)


• Solid PostgreSQL skills: schema design, performance tuning, migrations, connection pooling


• Experience operating live services: diagnosing issues from telemetry, rollback judgment


• Understanding of AI security boundaries — treating model/retrieved content as untrusted, enforcing authZ outside the model


• Comfort debugging across service boundaries using traces and correlation IDs


• Familiarity with retries, backoff, circuit breakers for rate-limited APIs


• Testing beyond unit tests — contract tests, eval of non-deterministic systems

Nice to Have

• Experience with vendor-to-in-house system handovers


• Azure (Container Apps, OpenAI deployments, Key Vault)


• Terraform/OpenTofu, CI/CD pipelines


• Vector search/RAG at scale, chunking, reranking


• LLM-as-judge evaluation awareness


• Guardrails frameworks (e.g., NeMo Guardrails)


• Modern React/TypeScript exposure


• Data privacy/retention engineering experience

Why Apply?

Join a high-impact engineering effort shaping how real users interact with complex operational data through AI — with strong ownership, modern tooling, and real production stakes.

? Ready to make an impact? Apply now to learn more about this opportunity.