GenAI & Agentic AI Lead Engineer

JPMorganChase; Glasgow; On-site; GBP 120,000 - 170,000; Full time

Job summary

J.P. Morgan is seeking an Applied AI/ML Lead Engineer to design and productionize Generative AI and Agentic AI solutions. You will work across GenAI, RAG, and tool-using agents, delivering production-grade services on AWS and cloud-native platforms.

The role emphasizes modern AI engineering workflows, strong software engineering fundamentals, and collaboration with cross-functional teams to turn complex AI concepts into reliable business applications.

Qualifications

• Undergrad or Master’s degree in CS, DS, ML or related field.
• Hands-on experience building applied AI/ML or GenAI solutions.
• Familiarity with MCP and agentic architectures.
• Proficient in Java or Python; building APIs/services.
• Experience on AWS and cloud-native environments.
• Strong SDLC, CI/CD, testing, and observability practices.

Responsibilities

• Design and deploy GenAI and Agentic AI solutions across business workflows.
• Build LLM/SLM-powered apps including RAG and tool-using agents.
• Develop production-grade services with Java and/or Python (REST/gRPC).
• Develop prompt strategies and automated evaluation to improve quality.
• Build data pipelines and ML workflows on cloud services.
• Apply MLOps across experimentation, versioning, deployment, monitoring.
• Implement testing, benchmarking, and observability for AI services.
• Collaborate with stakeholders to define requirements and success metrics.
• Navigate ambiguity with multiple stakeholders.

Skills

GenAI

LLMs

Python

Java

Microservices

MLOps

AWS

Education

Masters in CS/ML or related field

Tools

Docker

Kubernetes

REST APIs

GitHub Copilot

Claude Code

AWS SageMaker

Job description

J.P. Morgan is seeking an Applied AI/ML Lead Engineer to design and productionize Generative AI and Agentic AI solutions. You will work across GenAI, RAG, and tool-using agents, delivering production-grade services on AWS and cloud-native platforms.

The role emphasizes modern AI engineering workflows, strong software engineering fundamentals, and collaboration with cross-functional teams to turn complex AI concepts into reliable business applications.