Software Engineer III - AI/ML Platform Reliability

JPMorgan Chase & Co.

Glasgow

On-site

GBP 70,000 - 110,000

Full time

14 days+

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Job summary

JPMorganChase is seeking a Software Engineer III within the AI/ML Data Platforms organization to enhance reliability and scalability of AI/ML platforms. You will design, build, and maintain production-grade code and tooling, and collaborate across teams to deliver high-impact AI capabilities with operational excellence.

The role emphasizes observability, security, and resilience, with on-call responsibilities and a focus on scalable cloud-native infrastructure across Google Cloud, AWS, or Azure,

Qualifications

  • Formal training or certification on software engineering concepts and proficient applied experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in Python.
  • Proficiency in all aspects of the Software Development Life Cycle.
  • Experience with infrastructure-as-code and cloud-native delivery practices, including Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployment workflows.
  • Experience in designing and developing large-scale distributed systems and cloud-native architecture.
  • Experience building large scale infrastructure and cloud-native delivery in Google Cloud, AWS, or Azure and Terraform.
  • Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools with demonstrated ability to evaluate AI-generated outputs.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

Responsibilities

  • Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demands.
  • Own NFRs and develop tooling for observability, security, resilience, infrastructure management and operations excellence.
  • Build and maintain scalable infrastructure to support the deployment and operation of large-scale AI platforms and apps.
  • Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems.
  • Participates in on-call rotations and escalation workflows, Debug and solve issues in a production environment, take full ownership of problems, develop solutions.
  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Leverages enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity, while validating outputs through peer review, automated testing, and secure coding standards
  • Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
  • Adds to team culture of diversity, opportunity, inclusion, and respect

Skills

Python
System design
Application development
SDLC
Observability
AI-assisted development tools
Responsible AI
Distributed systems
Cloud platforms
CI/CD pipelines

Tools

Terraform
Kubernetes
OpenTelemetry
Dynatrace
Grafana
Cloud CI/CD tooling

Job description

Are you passionate about building resilient, scalable systems that power the future of AI? At JPMorganChase, we're pushing the boundaries of what's possible with artificial intelligence and machine learning - and we need engineers like you to help us do it reliably, securely, and at scale.

As a Software Engineer III at JPMorganChase within the AI/ML Data Platforms organization, you will be a key member of the Reliability Engineering team, contributing to the design and delivery of trusted, market-leading technology products. You will apply your technical expertise and problem-solving skills to enhance the reliability and scalability of AI/ML platforms, build reusable services and tooling, and partner across teams to unblock high-impact AI use cases. This is an opportunity to shape how the firm delivers AI capabilities - with operational excellence at the core.

Responsibilities:
  • Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast-growing demands.
  • Own NFRs and develop tooling for observability, security, resilience, infrastructure management and operations excellence.
  • Build and maintain scalable infrastructure to support the deployment and operation of large-scale AI platforms and apps.
  • Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems.
  • Participates in on-call rotations and escalation workflows, Debug and solve issues in a production environment, take full ownership of problems, develop solutions.
  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
  • Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts and proficient applied experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced proficiency in programming with Python.
  • Proficiency in all aspects of the Software Development Life Cycle.
  • Experience with infrastructure-as-code and cloud-native delivery practices, including tools such as Terraform, containers, Kubernetes, CI/CD pipelines, and automated deployment workflows.
  • Experience in designing and developing large-scale distributed systems and cloud-native architecture.
  • Experience building large scale infrastructure and and cloud-native delivery practice in Google Cloud, AWS, or Azure and Terraform.
  • Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services.
  • Systematic problem-solving and troubleshooting skills in a complex system.
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Preferred qualifications, capabilities, and skills
  • Prior experience working in AI Cloud Infrastructure.
  • Prior experience developing GenAI Apps or AI Agents.
  • Previous experience as an Infrastructure or Platform Software Engineer in a dynamic technology company or startup.
  • Self-managed, self-motivated with strong sense of ownership, urgency, and drive
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