AI Engineer – Production AI Features

About the role

We are looking for an AI Engineer to build production‑grade AI features for our enterprise products. This role focuses on delivering reliable, user‑facing systems such as retrieval‑augmented generation pipelines, agentic workflows, and LLM‑backed services.

Key responsibilities

• Develop and maintain RAG pipelines, agentic systems, and LLM‑powered services using Python, FastAPI, and modern vector stores (e.g., Pinecone, Chroma, pgvector).
• Design prompt strategies, evaluation harnesses, and guardrails to ensure production reliability and track quality with concrete metrics.
• Integrate LLM APIs (OpenAI, Anthropic, Hugging Face, or local inference) into product surfaces, selecting models based on cost, latency, and accuracy trade‑offs.
• Release features behind feature flags, instrument them, and iterate based on user signals and evaluation results.
• Collaborate with backend, frontend, and product teams on data pipelines, integration, and scoping while maintaining clear written communication.
• Document implementations so future engineers can extend them without additional guidance.

Required profile

• 3–5 years of professional software engineering experience, including at least one year hands‑on with LLMs or applied ML in production.
• Strong Python expertise and comfort with FastAPI or a comparable async framework and clean API design.
• Practical experience with at least one agentic framework such as LangChain, LlamaIndex, LangGraph, or CrewAI.
• Working knowledge of vector databases, embedding models, chunking strategies, and retrieval failure modes.
• Proficiency in SQL; PostgreSQL preferred; ability to write window functions unaided.
• Familiarity with Docker, Git, and at least one cloud platform (AWS, GCP, or Azure).

Required skills

• Python
• FastAPI
• Async programming
• LangChain / LlamaIndex / LangGraph / CrewAI
• Vector databases (Pinecone, Chroma, pgvector)
• LLM APIs (OpenAI, Anthropic, Hugging Face)
• SQL / PostgreSQL
• Docker
• Git
• AWS / GCP / Azure