Production AI Engineer for Banking LLMs & RAG (Remote)

Titan AI; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Equity

Remote work (US)

Travel to client sites occasionally

Job summary

Titan AI is seeking a software engineer with 5+ years of software experience and at least 2 years building and operating production AI systems. You will own agent workflows, RAG pipelines, and LLM integration layers, delivering reliable AI solutions for banking tasks.

Strong Python fundamentals, experience with LangChain/LangGraph, and vector databases are required. The role is remote within the US, with occasional travel to client sites.

Qualifications

• 5+ years software engineering; 2+ years building and shipping production agentic AI or RAG systems.
• Agent framework experience: LangChain, LangGraph, PydanticAI, AutoGen, or Semantic Kernel.
• RAG stack proficiency: embedding models, vector DBs (Pinecone, Weaviate, Milvus, FAISS), hybrid search, retrieval evaluation.
• LLM integration depth: tool calling, structured outputs, multi‑step reasoning, behavioral regression testing.
• AI eval and observability tooling: LangSmith, RAGAS, DeepEval, Arize, Langfuse, or equivalent.
• REST APIs, async Python, microservices; Azure cloud experience preferred.

Responsibilities

• Own production AI systems across agent workflows, retrieval pipelines, and LLM integration layers.
• Develop and maintain RAG pipelines for banking documents and workflows.
• Ensure reliable, auditable inference with production monitoring and observability.
• Build backend services and APIs powering client-facing AI products with bank-grade uptime.

Skills

Python

Async APIs

LangChain

LangGraph

RAG pipelines

LLM integration

Observability tooling

Tools

Pinecone

Weaviate

Milvus

FAISS

LangSmith

Langfuse

Arize

Job description

Titan AI is seeking a software engineer with 5+ years of software experience and at least 2 years building and operating production AI systems. You will own agent workflows, RAG pipelines, and LLM integration layers, delivering reliable AI solutions for banking tasks.

Strong Python fundamentals, experience with LangChain/LangGraph, and vector databases are required. The role is remote within the US, with occasional travel to client sites.