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Lead Software Engineer - Public Cloud, Foundational Infra Platforms

JPMorgan Chase
Glasgow, GBR
Full-time
Senior
Onsite
Discovered Today
AWSAzureGoogle CloudTerraformJavaPython
Free

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Job responsibilities

  • Develop secure, high-quality production code for cloud platform services and tooling, and review and debug code written by others
  • Own significant technical design decisions, contributing to product design, platform architecture, and the technical processes that keep the platform reliable
  • Build deep knowledge of the platform and share it deliberately, ensuring critical capabilities are never held by a single engineer
  • Mentor other engineers and help raise the engineering practices of the wider team
  • Contribute to the engineering community as an advocate of firmwide frameworks, tools, and practices across the Software Development Life Cycle
  • Influence peers and project decision-makers to consider the use and application of leading-edge technologies
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
  • 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
  • Foster a team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and advanced applied experience
  • Advanced proficiency in one or more programming languages such as Java, Python, or Go
  • Hands-on experience with at least one major public cloud — AWS, Azure, or Google Cloud
  • Hands-on experience with Terraform for infrastructure as code, applied from a software engineering perspective
  • Experience designing, developing, and maintaining production software systems consumed by other engineering teams
  • Experience owning technical design decisions and mentoring other engineers
  • Knowledge of cloud-native architecture, distributed systems, and microservices design patterns, including scalability, reliability, and fault tolerance
  • Proficiency across the Software Development Life Cycle, including design, development, testing, and deployment
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices

Preferred qualifications, capabilities, and skills

  • Experience engineering and supporting high-volume production platforms, including release engineering, continuous delivery, and automated testing strategy
  • Background in systems design and systems engineering at platform level, ideally including the full operational lifecycle — standing a platform up, running it, and recovering it
  • Depth in cloud identity, networking, and policy controls at enterprise scale
  • Breadth across more than one of AWS, Azure, and Google Cloud, or a track record of building platform abstractions that hold across providers
  • Experience delivering against regulatory or supervisory requirements in a regulated industry such as financial services
  • Comfort working in an environment where pairing and software teaming are common practices to foster collaboration and knowledge sharing

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