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 in the Networking Team at JPMorgan Chase within the Accelerator, 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.
To support our mission-critical systems and foster strong team collaboration, this position requires participation in our on-call rotation and working from the office 5 days per week.
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:
- Collaborate across the organisation to implement platform wide strategies in our networking stack.
- Optimise our infrastructure for failover and resiliency.
- Enhance our operator design and custom implementation: We are utilising a number of different cloud native operators. As our platform matures and scales, we need to ensure our custom operators remain fit for purpose.
- Improve observability of our networking components to meet SLOs.
- Lead troubleshooting of production workloads for customers and during incidents.
- Develop secure high-quality production code, and reviews and debugs code written by others.
- Lead 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
- Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
- Lead agile ceremonies
- Add 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.
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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 - Detailed understanding of public clouds and hands on knowledge on building cloud based environments.
- Expert knowledge of containerisation, Kubernetes and related tooling.
- Deep understanding of cloud-native and traditional networking architectures.
- Proven experience designing and operating scalable, secure and resilient networks in GCP or AWS.
- Strong understanding of networking fundamentals (TCP/IP, BGP, routing, DNS, NAT, Firewalls, IPAM, Load Balancers, VPN).
- Extensive experience writing and maintaining custom Kubernetes Operators in Golang.
- Capable of writing code to deliver highly automated infrastructure environments that support the wider organisation.
- Being comfortable in fast moving, critical environments and working with ambiguity
- 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
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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 - Hands on experience with Reconciliation Loops, ArgoCD, IaC tooling (Crossplane/Terraform) and Service Mesh (Istio)
- Experience Debugging Networking and Kubernetes issues across a large scale cloud native stack
- Direct connect, Cloud Interconnect, Partner Interconnect implementation
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