Senior GenAI Engineer

Look4IT

United States

Remote

USD 160,000 - 210,000

Full time

14 days+

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Benefits offered by this job

100% remote

B2B contract

Long-term engagement

Live LLM product

Modern AI/LLM stack

Flexible working environment

Job summary

Look4IT is seeking a Senior AI Engineer for a fully remote role building and operating a production-grade LLM system used by real users. You will drive end-to-end features from concept to deployment, focusing on answer quality, performance, observability and cost efficiency.

You will work with LangGraph, RAG, tool calling, Azure OpenAI, Gemini and Claude, shaping how AI-powered products are built and operated in production.

Qualifications

Experience building and operating backend services and APIs.
Hands-on production experience taking LLM features to live production.
Experience with cloud platforms, ideally Azure, and cost-aware optimization.
Familiarity with LangGraph, RAG, tool calling and streaming services.
Strong problem-solving, analytics and decision-making in production systems.

Responsibilities

Build end-to-end LLM-powered features and deploy as services with testing.
Own answer quality by evaluating prompts, models and retrieval pipelines.
Turn user questions into effective queries against search platforms and orchestrate loops.
Debug production, monitor latency, token use and cost budgets across model variants.

Skills

Backend development

APIs

Async programming

Testing

LLM production

LangGraph

RAG

Azure

English communication

Tools

LangGraph

Azure OpenAI

FAISS

PostgreSQL

Langfuse

Azure App Insights

Bicep

Docker/Podman

FastAPI

Python

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