Sr Lead AI Platform Engineer

JP Morgan Chase; Glasgow; On-site; GBP 62,000 - 102,000; Full time

Job summary

J.P. Morgan Chase is hiring a Senior VP Platform Engineer to design and own the platform, tooling, and infrastructure behind agentic AI/ML products. This full-time role is based within our Asset & Wealth Management business, offering a first-class approach and commitment to diversity and equal opportunity.

The role focuses on deploying pipelines, model serving, containerisation, and environment management while driving reliability and security across production AI/ML services.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Advanced proficiency in Python and infrastructure-as-code, with modern software engineering practices
• Deep hands-on experience with Kubernetes, containerisation, and cloud-native deployment patterns
• Strong CI/CD experience and a track record of building deployment and release automation
• Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)
• Practical experience with observability tooling (metrics, logging, tracing) and production incident response
• Experience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/performance management)
• Strong communication skills and the ability to set standards other engineers adopt
• Industry-recognised container/Kubernetes certification (e.g., CKAD or similar)
• Masters degree in Computer Science, Engineering, or a related technical field, or equivalent applied experience
• SRE experience and familiarity with reliability practices (SLOs, error budgets) is preferred
• Experience within financial services technology is preferred
• Familiarity with JPM-internal platform, cloud, and AI/ML infrastructure is preferred for internal candidates

Responsibilities

• Design and build our platform, including deployment pipelines, model serving, containerisation, orchestration, and environment management
• Set the standard for reliability, observability, and operational excellence across our production AI/ML services
• Build tooling and paved paths that help AI engineers ship agentic AI and ML products safely and quickly
• Implement platform-level security, secrets management, and access controls to firm-wide standards
• Partner with data and AI engineers to productionise models and coordinate with external infrastructure functions to reduce operational dependency and risk
• Lead capacity, cost, and performance management for our compute and inference workloads
• Mentor platform and DevOps engineers and set engineering standards through design and code review
• Champion our culture of diversity, opportunity, inclusion, and respect

Skills

Software engineering fundamentals

Communication

Leadership/mentoring

Problem solving

Education

Master's degree in Computer Science or Engineering

Tools

Python

Kubernetes

CI/CD

Job description

Salary: £62,000 - 102,000 per year

Requirements

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Advanced proficiency in Python and infrastructure-as-code, with modern software engineering practices
• Deep hands-on experience with Kubernetes, containerisation, and cloud-native deployment patterns
• Strong CI/CD experience and a track record of building deployment and release automation
• Experience serving, scaling, and monitoring ML models or data-intensive services in production (MLOps)
• Practical experience with observability tooling (metrics, logging, tracing) and production incident response
• Experience operating ML/LLM workloads in production (LLMOps, inference reliability, cost/performance management)
• Strong communication skills and the ability to set standards other engineers adopt
• Industry-recognised container/Kubernetes certification (e.g., CKAD or similar)
• Masters degree in Computer Science, Engineering, or a related technical field, or equivalent applied experience
• SRE experience and familiarity with reliability practices (SLOs, error budgets) is preferred
• Experience within financial services technology is preferred
• Familiarity with JPM-internal platform, cloud, and AI/ML infrastructure is preferred for internal candidates

Responsibilities

• Design and build our platform, including deployment pipelines, model serving, containerisation, orchestration, and environment management
• Set the standard for reliability, observability, and operational excellence across our production AI/ML services
• Build tooling and paved paths that help AI engineers ship agentic AI and ML products safely and quickly
• Implement platform-level security, secrets management, and access controls to firm-wide standards
• Partner with data and AI engineers to productionise models and coordinate with external infrastructure functions to reduce operational dependency and risk
• Lead capacity, cost, and performance management for our compute and inference workloads
• Mentor platform and DevOps engineers and set engineering standards through design and code review
• Champion our culture of diversity, opportunity, inclusion, and respect

Technologies

• Agentic AI
• AI
• CI/CD
• Cloud
• DevOps
• Kubernetes
• LLM
• Machine Learning
• MLOps
• Model Serving
• Python
• Security
• Network

More

We are J.P. Morgan Chase, a global leader in financial services, serving prominent corporations, governments, wealthy individuals, and institutional investors. Our International Private Bank Technology Artificial Intelligence and Machine Learning team is hiring a Senior VP Platform Engineer to help design and own the platform, tooling, and infrastructure behind our agentic AI and machine learning products. This is a full-time role based within our Asset & Wealth Management business. We offer a first-class business in a first-class way approach, value long-term client partnerships, and are committed to diversity, inclusion, and equal opportunity, with reasonable accommodations available where needed.

last updated 36 week of 2026