Applied AI Platform Engineer — ML & Full‑Stack

JPMorganChase; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorganChase seeks a Full Stack Engineer - ML Platform in its DocAI team to design and deliver production architectures for AI-powered products, blending software engineering with applied research to scale enterprise-grade AI securely.

You will collaborate with cloud and SRE teams, contributing to a team culture that values ownership, learning, and impact, with optional people leadership paths.

Qualifications

• Degree in Computer Science, Mathematics, or Statistics.
• Strong knowledge of Python and software engineering principles.
• Broad understanding of frontend/backend, cloud architecture, databases, security and networks.
• Experience with AWS and Kubernetes.
• Ability to develop and deploy business-critical, data-intensive applications.
• Understanding of CS fundamentals and development best practices.
• Ability to align ML problems with business objectives.

Responsibilities

• Design and deliver enterprise-grade machine learning systems.
• Implement distributed, multi-threaded, and scalable applications.
• Build, test, and deploy secure pipelines for cloud systems, desktop apps, and ML solutions.
• Apply software engineering and CS best practices.
• Develop and deploy data-intensive applications.
• Leverage reusable libraries and services across teams.
• Use MLOps tools for versioning, reproducibility, and observability.
• Collaborate with cloud and site reliability teams to build robust production architectures.

Skills

Python

AWS

Kubernetes

Frontend

Backend

Software stack understanding

CS fundamentals

Education

Quantitative degree (CS/Math/Stats)

Tools

Pydantic AI

Langraph

TypeScript

Kubernetes

Job description

JPMorganChase seeks a Full Stack Engineer - ML Platform in its DocAI team to design and deliver production architectures for AI-powered products, blending software engineering with applied research to scale enterprise-grade AI securely.

You will collaborate with cloud and SRE teams, contributing to a team culture that values ownership, learning, and impact, with optional people leadership paths.