Senior AI/ML Platform Reliability Engineer

J.P. MORGAN; Bournemouth; On-site; GBP 70,000 - 110,000; Full time

Job summary

JPMorganChase is seeking a Software Engineer III to join the AI/ML Data Platforms Reliability Engineering team in the UK. You will design and deliver trusted AI/ML platforms with strong observability, security, and scalable infrastructure to support large-scale deployments.

You will apply your Python expertise and SDLC knowledge to build reusable services and tooling, collaborate across teams, and participate in on-call workflows to ensure production reliability and resilience.

Qualifications

• Formal training or certification in software engineering concepts.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Experience with infrastructure-as-code and cloud-native delivery practices.

Responsibilities

• Design and implement solutions to enhance reliability and scalability of AI/ML platforms and applications.
• Own non-functional requirements and develop tooling for observability, security, resilience, and operations excellence.
• Build and maintain scalable infrastructure to support deployment and operation of large-scale AI platforms and apps.
• Participate in on-call rotations and take ownership of production issues; debug and resolve problems.

Skills

Python

Distributed systems

Observability

Problem solving

Security

Cloud concepts

Software design

OpenTelemetry

Dynatrace

Grafana

AI/ML tooling

Education

Formal training or certification in software engineering

Tools

Terraform

Kubernetes

CI/CD pipelines

OpenTelemetry

Dynatrace

Grafana

Job description

JPMorganChase is seeking a Software Engineer III to join the AI/ML Data Platforms Reliability Engineering team in the UK. You will design and deliver trusted AI/ML platforms with strong observability, security, and scalable infrastructure to support large-scale deployments.

You will apply your Python expertise and SDLC knowledge to build reusable services and tooling, collaborate across teams, and participate in on-call workflows to ensure production reliability and resilience.