Applied AI Engineer
Job Description
Key Responsibilities
- Design and build LLM-powered backend services/APIs (Python, FastAPI preferred)
- Design robust workflows with tool/function calling, retries, fallbacks, and guardrails
- Implement structured outputs with strong validation and schema-driven contracts
- Develop and maintain RAG pipelines with retrieval, ranking, and generation
- Write high-quality unit and integration tests, including LLM behavior regression tests
- Containerize and deploy services across dev/stage/prod environments
- Collaborate closely with product and engineering teams to ship iteratively
- Contribute to clean documentation, runbooks, and API contracts
Must-Have
- Strong Python and backend engineering fundamentals
- Experience with FastAPI (or similar) and RESTful API design
- Hands-on LLM integration experience (OpenAI, Anthropic, Azure OpenAI, etc.)
- Solid testing practices (pytest, mocking, integration tests)
- Working knowledge of Docker, Git, and CI pipelines
Good-to-Have
- Experience with vector databases and embeddings (FAISS, Pinecone, pgvector, etc.)
- Exposure to observability (logging, metrics, tracing)
- Cloud experience (AWS/Azure/GCP)
- Familiarity with async workflows and background job patterns
- Experience with TypeScript/React
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