Lead Software Engineer - Cloud Platform Engineering
JPMorgan Chase · London, United Kingdom · 2mo ago
Out of the successful launch of Chase in 2021, we’re a new team, with a new mission. We’re creating products that solve real world problems and put customers at the center - all in an environment that nurtures skills and helps you realize your potential. Our team is key to our success. We’re people-first. We value collaboration, curiosity and commitment.
As a Platform Engineer at JPMorgan Chase within the Accelerator Business Platform Team, you are the heart of this venture, focused on getting smart ideas into the hands of our customers. You have a curious mindset, thrive in collaborative squads, and are passionate about new technology. By your nature, you are also solution-oriented, commercially savvy and have a head for fintech. You thrive in working in tribes and squads that focus on specific products and projects – and depending on your strengths and interests, you'll have the opportunity to move between them.
While we’re looking for professional skills, culture is just as important to us. We understand that everyone's unique – and that diversity of thought, experience and background is what makes a good team, great. By bringing people with different points of view together, we can represent everyone and truly reflect the communities we serve. This way, there's scope for you to make a huge difference – on us as a company, and on our clients and business partners around the world
Job responsibilities
- Develops secure high-quality production code, and reviews and debugs code written by others
- Develops composable infrastructure systems and capabilities
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Provide operational support for production systems in a “you-build-it-you-run-it” culture, including incident response and continuous reliability improvements.
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Adds to team culture of diversity, equity, inclusion, and respect
- Designs, builds, and operates Kubernetes-based platform services, automates developer self-service and CI/CD, improves reliability and operational readiness, and strengthens platform security and controls via IaC, policy-as-code, and hardening standards.
- 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.
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts, such as Certified Kubernetes Application Developer (CKAD), Google Associate Cloud Engineer Certification, or AWS Certified Solutions Architect
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s), such as Go, Java or Kotlin
- Advanced understanding of agile methodologies, CI/CD, application resiliency, and security
- Demonstrated proficiency in software applications and processes within a technical domain, such as cloud, artificial intelligence, machine learning, mobile, etc.
- Practical cloud native experience, deploying Kubernetes applications on a cloud service provider, such as Google Cloud, Amazon Web Services, or Microsoft Azure
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred qualifications, capabilities, and skills
- Expertise in the Kubernetes operator pattern
- Expertise deploying infrastructure as code, using Crossplane, Terraform, or equivalent
- Experience with GitOps workflows
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