Applied AI ML Lead Software Engineer, LLM Suite Engineering

JPMorgan Chase

Quick summary

Work type
On-site
Location
London, Greater London, United Kingdom
Posted
6 days ago
Nearby
72 roles within 25 mi

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How this pay compares to similar roles

Similar $200k
$156k most similar roles pay here $243k

This listing doesn't post a salary. Most similar roles pay $165,825–$235,000.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 439 open roles on FindRole.

Listed pay typically runs $148,625–$212,500 across 228 roles with salary data.

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At a glance

TL;DR · Applied AI ML Lead Software Engineer, LLM Suite Engineering

Role Posting Log in to save

As an Applied AI ML Lead Software Engineer in the LLM Suite Engineering team at JPMorganChase, you will lead the design and implementation of production-grade AI/ML solutions that integrate with existing systems. Your day-to-day involves architecting complex applications, developing GenAI services using Azure OpenAI models and AWS Bedrock, and ensuring operational stability through secure coding practices. You will collaborate closely with peers to identify patterns and improve standards for reliability and scalability, leveraging modern public cloud services and agentic frameworks. Essential skills include proficiency in Python (FastAPI), experience with microservices and APIs, and knowledge of containerization, CI/CD pipelines, and security best practices. This role demands a strong background in system design, application development, and operational stability within a large corporate environment.

Skills

Python FastAPI Azure AWS GenAI CI/CD NoSQL Docker Kubernetes Messaging Queues LangGraph Model Context Protocol Agentic Orchestration A2A Communication AWS Bedrock Azure OpenAI

What you'll do

  • Design and deliver production-grade AI/ML solutions for the LLM Suite platform.
  • Build agentic systems using public cloud architecture (Azure, AWS) and modern frameworks.
  • Write secure, high-quality code that integrates with existing enterprise systems.
  • Identify patterns in data to improve coding standards and system reliability.
  • Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock.

What we're looking for

  • Hands-on experience with system design and application development in a corporate environment.
  • Proficiency in Python (FastAPI) and building microservices and APIs.
  • Experience with public cloud architecture (Azure, AWS) and GenAI services.
  • Strong understanding of CI/CD, application resiliency, and security practices.
  • Knowledge of agent-to-agent communication concepts and Model Context Protocol.
  • Familiarity with agentic orchestrators and developing personal AI assistants.
  • Expertise in containerization and working with large language models.

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