Job description
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 Benefits B2B contract 100% remote work Long-term engagement Work on a live LLM product Modern AI/LLM technology stack Flexible working environmentThis 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.
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.Senior AI EngineerResponsibilities: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.