Senior AI Engineer (Hybrid) - LLM & RAG Architect

Talentify; Los Angeles (CA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health benefits

Referral program

Growth opportunities

Job summary

Talentify is seeking a Senior AI Engineer in Woodland Hills, CA with a hybrid work setup. You will design and build production-grade LLM-powered applications, architect end-to-end AI workflows, and implement RAG pipelines across enterprise data.

Strong Python/JavaScript skills and experience with LangChain, LangGraph, and cloud integration are required. The role focuses on tooling agents, API integration, and scalable backend systems, with emphasis on performance, reliability, and cost

Qualifications

• Strong programming experience in Python and JavaScript.
• Experience with LangGraph, LangChain, RAG architectures and embeddings.
• Experience integrating AI systems with APIs, backend services, and cloud platforms.
• Hands-on development of production-grade backend systems with LLMs.
• Prompt engineering and orchestration for LLM-based apps.

Responsibilities

• Design and build production-grade LLM-powered applications and agentic systems from architecture to deployment.
• Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python.
• Design and implement RAG pipelines over enterprise data using embeddings and vector databases.
• Build multi-step, tool-using agents (planning, execution, memory) using LangChain or LangGraph.
• Integrate AI systems with APIs, backend services, and cloud platforms.
• Establish evaluation, reliability, and performance strategies (accuracy, latency, cost).

Skills

Python

JavaScript

LangGraph

LangChain

RAG architectures

Embeddings

Vector databases

APIs

Cloud platforms

System design

Tools

LangChain

LangGraph

AutoGen

Job description

Talentify is seeking a Senior AI Engineer in Woodland Hills, CA with a hybrid work setup. You will design and build production-grade LLM-powered applications, architect end-to-end AI workflows, and implement RAG pipelines across enterprise data.

Strong Python/JavaScript skills and experience with LangChain, LangGraph, and cloud integration are required. The role focuses on tooling agents, API integration, and scalable backend systems, with emphasis on performance, reliability, and cost