Principal Software Engineer, Cloud Platform (DevEx & AI Platform Automation)

Join a forward-thinking team at JPMorganChase and help shape the future of cloud platform engineering. As a Principal Software Engineer, you’ll play a critical role in building and optimizing the platforms that power our data and AI initiatives. You’ll collaborate with talented engineers and stakeholders to deliver solutions that are secure, reliable, and scalable. This is your opportunity to influence technology strategy, drive operational excellence, and make a tangible impact across the organization. If you’re passionate about cloud, automation, and enabling next-generation AI/ML capabilities, we want to hear from you.

As a Principal Software Engineer at JPMorgan Chase in the Chief Data and Analytics Office’s Data Platforms division, you will lead the technical direction for cloud platform engineering. You will work with cross-functional teams to design, build, and operate innovative cloud platform solutions. You will help us deliver secure, scalable, and reliable platforms that support our AI/ML and data-driven initiatives. Your expertise will drive performance, efficiency, and a best-in-class developer experience across our engineering organization. You will also help advance our AI-assisted development practices, and efforts on Agentic/AIOps by leveraging modern AI coding tools and agent frameworks to accelerate engineering velocity and platform innovation at scale.

Job responsibilities

• Provide technical leadership and guidance to the cloud engineering team.
• Lead the design and development of secure, scalable, and reliable cloud infrastructure and platform tools.
• Drive adoption of modern DevEx (Developer Experience) practices and evolve CI/CD and developer tooling to improve delivery speed, quality, and consistency.
• Align platform strategy and roadmaps with business priorities; lead cross-functional initiatives to modernize SDLC practices.
• Evaluate, integrate, and govern strategic tooling to reduce cognitive load and improve developer experience.
• Collaborate with development teams to identify and eliminate bottlenecks on the platform.
• Define and promote paved paths and self-service workflows to streamline developer workflows.
• Implement real-time telemetry pipelines and workflows for large-scale platform observability and analytics.
• Champion adoption of tools that can improve developer productivity through clear documentation, training, office hours, and close engagement with the developer community.
• Standardize use of AI-assisted coding tools and AI-powered development ecosystems to accelerate development workflows, code generation, and engineering productivity across the organization.
• Contribute to the design and development of AI agents and Model Context Protocol (MCP) integrations using frameworks built on top of Google ADK, Anthropic SDKs, etc. and related tooling to enable intelligent, scalable platform automation.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience
• Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP).
• Advanced knowledge of containerization and orchestration platforms (Docker, Kubernetes, ECS, etc.).
• Demonstrated expertise in DevEx (Developer Experience) and CI/CD tools (Jenkins, Spinnaker, Bitbucket, GitHub, etc.).
• Strong knowledge of cloud security best practices, shift-left methodologies, and DevSecOps processes.
• Strong programming skills in Golang or Python, with a solid understanding of software development best practices.
• Proficiency with cloud infrastructure provisioning tools (Terraform, KRO, Crossplane, etc.).
• Experience with logging and monitoring tools (Splunk, Grafana, Datadog, Prometheus, etc.).
• Deep understanding of cloud infrastructure design, architecture, and migration strategies.
• Demonstrated proficiency with AI-assisted coding workflows, including experience with LLM-powered development tools, spec-driven development methodologies, and prompt engineering for software engineering use cases.

Preferred qualifications, capabilities, and skills

• Master’s degree in a related field and certifications in Cloud, Kubernetes, or infrastructure-as-code technologies.
• Experience implementing multi-cloud architectures and leading end-to-end platform development efforts.
• Background in designing and developing scalable AI/ML or Data platforms.
• Experience with automation and workflow orchestration…