Gen AI Senior Engineer

secure, observable, cost-efficient production

What Youll Do

• Convert research POCs into

  production-grade

  services with SLAs, on-call readiness, and guardrails.
• Design and ship

  agentic workflows

  (tool use, function calling, orchestration graphs, retries, fallbacks).
• Build robust

  RAG

  pipelines: ingestion chunking indexing retrieval re-ranking grounded generation.
• Implement

  evaluation & LLMOps

  : golden sets, regression tests, CI eval gates, telemetry dashboards, A/B and canarying.
• Build and document

  FastAPI

  backends (async, OpenAPI, pagination, rate limits, idempotency, background jobs).
• Add

  observability

  (OpenTelemetry, logs/metrics/traces, cost & token spend) and performance/cost tuning.

Minimum Qualifications

• 5+ years building production web apps/services; 2+ years with LLMs/RAG/agents.
• Proven

  end-to-end

  ownership: shipped at least one LLM/Agent system to real users.
• Strong

  Python

  (3.10+),

  FastAPI

  , async patterns;

  TypeScript

  with

  React/Next.js

  .
• Solid

  RAG

  fundamentals (indexing, embeddings, hybrid search, re-ranking, evals) and

  Agent

  patterns (tooling, retries, timeouts, circuit breakers).
• Experience with

  vector databases

  (pgvector/Milvus/Weaviate) and

  Postgres

  .
• CI/CD (GitHub Actions), Containers/K8s, IaC (Terraform), and cloud (AWS/Azure/GCP).
• Testing discipline: unit/integration/e2e, load tests, contract tests; strong debugging & profiling.
• Clear communication, product sense, and trade-off thinking (latency/cost/quality/safety).

Preferred Qualifications

• LangGraph/CrewAI/AutoGen (or equivalent) for multi-agent orchestration; tool calling best practices.
• Retrieval evaluation with

  RAGAS/TruLens

  , custom golden sets, offline sims/trace replay.
• Prompt/version control, dataset/versioning, and experiment tracking; feature flags & canary deploys.
• Frontend polish: accessibility, performance budgets, error/retry UX, React Query/Zustand.
• Security reviews for LLMs/agents (prompt injection, data exfiltration, DLP, policy enforcement).