Senior Full Stack AI Engineer (Python, React, LLM, LangChain/LangGraph)
Location: Atlanta, GA (Remote - Any in USA - Remote is okay but might need some travels)
Duration: 6 monthsWe are building an enterprise Agentic AI platform for a Fortune 500 customer, operating in a U.S. export-controlled, SOX-regulated environment. We are hiring a Senior Fullstack Engineer with strong Python and React skills and hands-on experience building applications with LLMs and agentic frameworks like LangChain and LangGraph.
You will work alongside platform, data, and product engineers in a compliance-first environment to deliver agentic features that are reliable, observable, and safe to deploy in a regulated enterprise.
What You''ll Do
Build agentic AI features end-to-end — from prompt design and tool integration on the backend to streaming, interactive UIs on the frontend.
Design and implement agent workflows using LangChain, LangGraph, or equivalent frameworks — including multi-step reasoning, tool/function calling, memory, and human-in-the-loop checkpoints.
Build retrieval-augmented generation (RAG) pipelines — chunking, embedding, retrieval, reranking — and own the eval loop that tells us whether they''re actually working.
Develop Python backend services (FastAPI) that expose AI capabilities as APIs — including streaming endpoints (SSE/WebSocket), background job orchestration for long-running agent runs, and integrations with enterprise systems.
Build React/TypeScript frontends for AI-powered workflows — chat interfaces, tool-call rendering, document workflows, dashboards, and forms that handle streaming and partial state cleanly.
Own evals and observability for AI features — model performance tracking, token/cost monitoring, prompt and response logging (with appropriate PII handling), and regression suites.
Integrate multiple model providers (OpenAI, Anthropic, open-source models via vLLM/TGI, etc.) behind clean abstractions, with awareness of latency, cost, and failure modes.
Partner with product and data teams on feature design, evaluation criteria, and rollout strategy.
Write tests, do code reviews, and contribute to engineering standards in a compliance-controlled environment.
8+ years of professional software engineering experience, including production ownership.
Strong Python backend experience. Comfortable with FastAPI (or equivalent), async/await, SQLAlchemy, Pydantic, and packaging Python services for production.
Hands-on experience building LLM-powered applications in Python. You''ve shipped real features — not just notebooks — using LLM APIs (OpenAI, Anthropic, or open-source models). You understand tokens, context windows, structured outputs, function calling, and streaming.
Hands-on experience with agentic AI frameworks — LangChain, LangGraph, LlamaIndex, or equivalent. You can articulate when each is the right tool and when they''re not. You''ve designed and debugged multi-step agent workflows in production.
Experience with RAG pipelines — embeddings, vector databases (pgvector, Qdrant, Weaviate, Milvus, FAISS, or similar), retrieval and reranking strategies, and how to evaluate retrieval quality.
Strong React frontend experience with TypeScript. You understand hooks, state management (TanStack Query, Zustand, Redux Toolkit), and how to build performant interfaces. You''ve built UIs that consume streaming APIs.
API design experience — REST and OpenAPI, with attention to versioning, error contracts, and clear documentation.
Database fluency — schema design, indexes, migrations, transactions.
Testing discipline — unit, integration, and (for AI features) eval/regression tests.
Git, CI/CD, and code review as routine.
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