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Salary
≈ $136k – $235k per year (Estimated)
Location
In office (London)
Seniority
Staff

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Jul 13, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

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 Senior Lead Software Engineer (Platform) 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. In this senior lead role, you set technical direction across squads, raise engineering standards, and mentor and grow other technical leaders.

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

- Sets technical direction for platform engineering across squads, aligning architecture, delivery, and operational excellence to business outcomes and risk controls.

- Develops secure high-quality production code, and reviews and debugs code written by others; establishes engineering standards and best practices.

- Designs and develops composable infrastructure systems and capabilities, with a focus on scalable platform services.

- Designs, builds, and operates Kubernetes-based platform services; automates developer self-service and CI/CD; improves reliability and operational readiness; strengthens platform security and controls via IaC, policy-as-code, and hardening standards.

- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.

- Provides operational support and leadership for production systems in a "you-build-it-you-run-it" culture, including incident response, post-incident learning, 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 and grows communities of practice across Software Engineering to drive awareness, adoption, and use of new and leading-edge technologies.

- Coaches and mentors engineers, developing technical leadership capability and supporting high performance across teams.

- Adds to team culture of diversity, equity, inclusion, and respect.

  • Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

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, or equivalent experience.

- Hands-on practical experience delivering system design, application development, testing, and operational stability, including leading technical delivery in complex environments.

- 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, including setting standards and driving adoption across teams.

- 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, at meaningful scale.

  • Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.

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.

#ICBCareer #ICBEngineering

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