Job description
This is a remote position.
We are looking for a Senior AI Engineerto 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 environment
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.