LLM Applications Engineer

  • New York, New York, United States
  • Full-Time
  • On-Site
  • 130,000-175,000 USD / Year
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Job Description:

LLM Applications Engineer

Location: New York | San Francisco | Munich | London (In-Person)
Employment Type: Full-Time
Base Salary: $130,000 – $175,000

Overview

We are hiring an LLM Applications Engineer to build and deploy production-grade LLM-powered systems.

This is a hybrid AI infrastructure and product engineering role. You will design and implement RAG pipelines, vector retrieval systems, agentic workflows, and full-stack LLM-powered product experiences. The role requires hands-on ownership across backend Python systems and React-based frontend applications.

This position is for engineers who move beyond prototypes and ship robust, scalable LLM systems into production.

What Youll Do

  • Design and deploy production-grade RAG (Retrieval-Augmented Generation) pipelines
  • Build and optimize vector retrieval systems
  • Implement agentic LLM workflows and orchestration layers
  • Develop full-stack product experiences powered by LLMs
  • Design clean, scalable APIs and asynchronous processing systems
  • Connect LLM systems to structured data sources, including SQL databases and data engines
  • Collaborate closely with product and engineering teams to ship LLM-first features

What Were Looking For

Core Requirements

  • 2+ years of full-stack web development experience
  • Proficiency in Python and JavaScript or TypeScript
  • Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or Haystack
  • Hands-on experience building production RAG pipelines and retrieval systems
  • Strong API design and asynchronous processing fundamentals
  • Ability to operate across backend infrastructure and frontend UI
  • Computer Science degree from a top-tier program

Strong Plus

  • Built and deployed RAG pipelines in live production environments
  • Experience working with scientific, technical, or research datasets
  • Strong product mindset with LLM-first feature development
  • Experience integrating LLM systems with SQL databases and broader data infrastructure

Who This Is Not For

This role is not a fit if you:

  • Have only academic or prototype-level LLM exposure
  • Have exclusively backend-only or frontend-only experience
  • Lack experience with vector databases or retrieval systems
  • Have not deployed LLM systems into production environments

What Success Looks Like

  • Production-grade RAG pipelines running reliably at scale
  • Clean, well-architected retrieval and orchestration systems
  • Seamless integration between LLM backends and frontend product experiences
  • Measurable product impact from LLM-powered features
  • Ownership of end-to-end LLM application architecture

Why This Role Is Unique

This is not a research-only AI role and not a traditional full-stack position.

You will sit at the intersection of AI infrastructure and product, building systems that combine retrieval, orchestration, and real-world user interfaces. If you want to ship meaningful LLM-powered products — not just experiment with models — this is an opportunity to own that architecture end to end.