Senior GenAI Engineer

This is a remote position.

• 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
  

• Azure OpenAI, AI Search, App Service
  
• Infrastructure-as-code (Bicep)
  
• Mentoring or tech-lead experience
  

• 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 environment