The Role
Build and operate production-grade LLM features using agentic workflows, RAG, tool calling, and cloud services. Develop FastAPI APIs, evaluation and regression systems, tracing, and observability. Improve answer quality, retrieval, prompts, latency, reliability, and cost through production debugging and model routing. Collaborate on technical decisions and potentially mentor or lead others.
Summary Generated by Built In
This is a remote position.
We are looking for a Senior AI Engineer to join a team building and operating a production-grade LLM system used by real users. This is not a proof-of-concept project.
You will be responsible for taking LLM-powered features from idea through development and deployment to continuous improvement, with a strong focus on answer quality, performance, observability and cost efficiency. You will work with modern LLM technologies, including LangGraph, RAG, tool calling, Azure OpenAI, Gemini and Claude, and have a real impact on how AI-powered products are built and operated in production.
Responsibilities:
- Build LLM-powered features end to end. Design and implement agentic flows, retrieval, and tool calling using LangGraph - then ship them as FastAPI services with streaming, persistence and proper tests.
- Own answer quality. Build evaluation datasets, regression suites and LLM-as-judge checks so we know whether a prompt or model change made things better before it reaches users.
- Get the right context to the model. Turn user questions into effective queries against our search platform, orchestrate multi-step research loops, and shape the context the model reasons over. When an answer is wrong, work out whether retrieval, the query or the prompt is at fault - and fix the right one.
- Debug production. Instrument flows with tracing (Langfuse), investigate bad answers from real traces, and manage latency, token and cost budgets - including routing across model sizes and families behind an AI gateway.
Requirements
- Experience in building and operating backend services - APIs, async, testing
- Hands-on experience taking LLM features to production and keeping them running - not only prototypes
- Agent / orchestration frameworks - LangGraph ideally
- Practical RAG experience
- Experience debugging LLM systems in production - tracing, evaluation, cost and latency
- Experience running services in the cloud (we're on Azure)
- Strong problem-solving skills, analytical thinking, and technical decision-making
- Fluent in English, proactive communicator, and a collaborative team player
- Open-minded, creative, and motivated to push boundaries in AI and automation
Nice to have:
- Azure OpenAI, AI Search, App Service
- Infrastructure-as-code (Bicep)
- Mentoring or tech-lead experience
- Tech stack:
- Python
- FastAPI
- LangGraph
- Azure OpenAI, Google Gemini, Anthropic Claude
- FAISS
- PostgreSQL
- Langfuse
- Azure App Insights
- Bicep
- Docker/Podman
Skills Required
- Experience building and operating backend services, including APIs, asynchronous programming, and testing
- Hands-on experience taking LLM features to production and operating them beyond prototypes
- Experience with agent or orchestration frameworks, ideally LangGraph
- Practical retrieval-augmented generation experience
- Experience debugging production LLM systems, including tracing, evaluation, cost, and latency
- Experience running services in the cloud, preferably Azure
- Strong problem-solving, analytical thinking, and technical decision-making skills
- Fluent English communication
- Proactive communication and collaborative teamwork
- Open-minded, creative, and motivated approach to AI and automation
- Experience with Azure OpenAI, Azure AI Search, or Azure App Service
- Experience with infrastructure as code using Bicep
- Mentoring or technical leadership experience
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The Company
What We Do
Look4IT is a recruitment agency specializing in providing top-quality recruitment and outsourcing services within the IT sector, focusing on staffing solutions for permanent and contract positions.
