Senior AI Engineer: Full-Stack, RAG & LLM Pipelines

BairesDev; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Remote-first company

USD salary or local currency

Home-office setup provided

Flexible hours

Parental leave & holidays

Mentorship & growth

Job summary

BairesDev is seeking a Senior Full Stack AI Engineer to own features end-to-end—from agent and skill integrations to RAG pipelines and API services. You will evaluate agent behavior against gold datasets and build robust validation before production.

Collaboration with senior engineers and proactive problem-solving are key parts of this role. You will integrate LLMs, design RAG pipelines over structured and unstructured data, and develop frontend interfaces with React and TypeScript.

Qualifications

• 5+ years of Python development experience.
• Experience with LLM integration and RAG pipelines using LangChain, LangGraph, or LlamaIndex.
• Experience with LLM evaluation, including LangSmith, LLM-as-judge, offline evals, or golden datasets.
• Experience with AWS.
• Working proficiency with React and TypeScript.
• Experience with retrieval over structured and unstructured data.
• Experience integrating agents and skills against internal services.
• Experience with vector search and embedding strategy using Pinecone, FAISS, Qdrant, or pgvector.
• Experience with container orchestration (ECS/EKS) and microservices.
• Strong prompt engineering skills, iterating against measured output.
• Experience with CI/CD and service observability, including logging, tracing, and SLOs.
• Upper-intermediate English proficiency.

Responsibilities

• Own features end to end, including agent and skill integrations, RAG pipelines, and supporting API services.

Skills

Python

LLM integration

LLM evaluation

React

TypeScript

Vector search

AWS

English

Tools

LangChain

LangGraph

LlamaIndex

LangSmith

Pinecone

FAISS

Qdrant

pgvector

ECS/EKS

CI/CD

Job description

BairesDev is seeking a Senior Full Stack AI Engineer to own features end-to-end—from agent and skill integrations to RAG pipelines and API services. You will evaluate agent behavior against gold datasets and build robust validation before production.

Collaboration with senior engineers and proactive problem-solving are key parts of this role. You will integrate LLMs, design RAG pipelines over structured and unstructured data, and develop frontend interfaces with React and TypeScript.