Infrastructure Cloud Engineer - DevOps, Python, Platform engineer- Lead Software Engineer

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 250,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer within Corporate Technology to drive high-impact, scalable technology initiatives in a fast‑paced, secure environment.

You will be a core technical contributor shaping architecture, leading AI-assisted engineering practices, and delivering production-grade solutions across cloud-native platforms, while mentoring teams and advancing engineering standards.

Qualifications

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Production Kubernetes depth — cloud-managed and on-prem.
• AWS at platform scale, multi-account.
• Infrastructure-as-Code — Terraform required.
• CI/CD & progressive delivery.
• Production operational stability, SRE mindset.
• Some coding experience for internal tooling.
• Experience using AI-assisted software development tools.
• Strong understanding of responsible AI use in engineering workflows.
• Proficient in all aspects of the Software Development Life Cycle.

Responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
• Develops secure high-quality production code, and reviews and debugs code written by others.
• Drives adoption of AI-assisted engineering practices to improve code quality and delivery.
• Applies knowledge of tools within the SDLC toolchain to improve automation.
• Identifies opportunities to automate remediation to improve stability.
• Leads evaluation sessions with external vendors, startups, and internal teams on architectural designs.
• Leads communities of practice across Software Engineering to drive awareness of new technologies.
• Adds to team culture of diversity, inclusion, and respect.

Skills

Kubernetes depth

AWS platform scale

Terraform

CI/CD

SRE mindset

Internal tooling scripting

AI-assisted development tools

Responsible AI practices

SDLC proficiency

Software engineering fundamentals

Tools

Terraform

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the Corporate Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• 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, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Production Kubernetes depth — cloud-managed and on-prem.Runs and troubleshoots K8s at theplatformlayer, not just "deploys to it": cluster add-ons and their failure modes (cert-manager, admission control, policy-as-code, GitOps, Helm, ingress & load-balancer controllers), RBAC, and control-plane, webhook issues.
• AWS at platform scale, multi-account.EKS, networking (VPC, load balancing, DNS), IAM, KMS secrets, and managed data stores. Fluent across resiliency patterns generally — multi-region, active active, active passive, failover, and cell-based designs.
• Infrastructure-as-Code — Terraform required.Solid hands-on Terraform: module-based, disciplined plan, apply, and safe change management.
• CI/CD & progressive delivery.End-to-end pipeline ownership — blue, green and cell-based rollouts, GitOps, artifact build, and orchestration (e.g., Spinnaker, Jenkins) — with strong safe-rollout and rollback judgment.
• Production operational stability, SRE mindset.Incident response, root-cause analysis, resiliency, observability-driven debugging, reducing toil, and hardening production.
• Some coding experience for internal tooling.Able to write scripts/automation and small internal tools (language-agnostic) to improve the platform — not a deep hands-on IC requirement, just practical coding fluency.
• 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
• Proficient in all aspects of the Software Development Life Cycle

Preferred qualifications, capabilities, and skills

• IAM customer-authentication knowledge— ForgeRock (AM, DS) or PingFederate, OAuth2, OIDC, SAML, PKI cert lifecycle. Helpful, but a strong platform engineer who ramps on our stack is fine.
• Resiliency chaos engineering (Game Days, fault injection).
• Secrets management (Vault, KMS, Secrets Manager). Observability depth (Splunk, Dynatrace).
• Managed database ops (Aurora, RDS, DB-change automation).
• On-prem cloud migration experience.
• "Platform-as-a-product" experience — owning a platform other engineering teams depend on.

• Certs as signal (not gates): AWS Solutions Architect, DevOps Pro, CKA, CKAD, ForgeRock, Ping.