Applied AI ML Senior Associate in LLM Suite Engineering

About

Help shape how intelligent systems are built and delivered at JPMorganChase. In this role, you’ll contribute to the LLM Suite platform by building AI/ML and agentic capabilities that are secure, reliable, and ready for production. You’ll collaborate closely with senior engineers, learn through real design discussions, and grow your technical depth across cloud and modern AI frameworks. If you enjoy solving tough problems and iterating quickly with feedback, you’ll fit right in.

As an Applied AI ML Senior Associate in LLM Suite Engineering, you will design, build, and troubleshoot software that enables AI/ML and agentic experiences on the platform. You will write secure, high-quality code and support algorithms that integrate with existing systems. You will collaborate with senior engineers on designs and implementation choices, focusing on reliability and operational stability. You will help deliver GenAI services using public cloud capabilities. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. You will contribute as a team player who seeks and applies feedback.

Responsibilities

• Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges
• Write secure, high-quality production code and maintain algorithms that integrate with existing systems
• Collaborate with senior engineers and participate in design discussions
• Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks
• Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock
• Collaborate openly with the team, seek feedback, and apply it to improve outcomes

Qualifications

Required Qualifications, Capabilities, and Skills

• Computer science degree or equivalent practical experience
• Hands-on experience with system design, application development, testing, and operational stability
• Strong understanding of the Software Development Life Cycle

Preferred Qualifications, Capabilities, and Skills

• Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock
• Proficiency in Python (FastAPI)
• Experience building microservices and APIs
• Experience with elastic compute, NoSQL databases, and messaging queues
• Proficiency working with large language models and building agents with LangGraph
• Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages, including containerization
• Knowledge of agent-to-agent (A2A) communication, Model Context Protocol (MCP), AI skills development, personal AI assistants, or agentic orchestrators