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 Principal Software Engineer at JPMorgan Chase within the Accelerator Business in the 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
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Work with senior stakeholders to define and drive the multi-year technical roadmap and long-term architectural strategy for platform engineering, ensuring competitive advantage and scalability.
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Mentor and coach senior engineers across teams, elevating the technical bar and championing Software Engineering Communities of Practice.
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Serve as the key technical liaison for product, business, and security stakeholders, translating technical decisions into business impact.
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Lead the design and delivery of composable, secure, and scalable infrastructure systems and capabilities.
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Own the operational stability of production systems ("You Build It, You Run It"), automating recurring issues and establishing DORA/SLIs/SLOs metrics for continuous improvement.
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Drive architectural standards and best practices across the organisation, leading technical evaluations with internal and external partners.
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Champion FinOps principles to drive significant cloud cost optimisation and guide performance tuning of distributed systems.
- Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
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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 at scale.
Required qualifications, capabilities, and skills
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Formal training or certification (e.g., BSc, CKAD, Google Associate Cloud Engineer, or AWS Certified Solutions Architect).
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Expert-level administration of a major cloud platform (GCP, AWS, or Azure).
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Mastery of Kubernetes administration and operator patterns.
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Strong cloud networking expertise across the OSI networking model.
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Strong proficiency in Infrastructure as Code (IaC) methodologies.
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Proven, hands-on experience in system design, development, testing, and operational stability.
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Advanced proficiency in modern language(s) (e.g., Go, Java, Kotlin).
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Demonstrated technical leadership and cross-team collaboration.
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Hands-on Security Engineering experience.
- Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
- Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
Preferred qualifications, capabilities, and skills
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Advanced knowledge ofCI/CD, application resiliency, and secure delivery (e.g., SLSA framework and GitOps).
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Deep experience with Observability and Monitoring tools (e.g., Prometheus, Grafana, OTEL).
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Expertise in performance optimisation of distributed systems (e.g., caching, network latency).
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Practical experience with Service Mesh technologies (e.g., Istio, Linkerd, Cillium).
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Demonstrated success in Mentorship and Coaching both senior and junior engineers.
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Proven ability in Technical Roadmapping and defining long-term platform strategy.
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Stakeholder management and communication skills.
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