Principal Software Engineer, Cloud Platform

JPMorgan Chase JPMorgan Chase · Banking · Palo Alto, CA +1 · Corporate Sector

This role focuses on building and optimizing cloud platforms that support data and AI initiatives within JPMorgan Chase. The Principal Software Engineer will lead technical direction for cloud platform engineering, focusing on secure, scalable, and reliable infrastructure. Key responsibilities include driving DevEx, CI/CD, evaluating tooling, implementing telemetry, and standardizing AI-assisted coding tools and AI agents for platform automation. While the role supports AI/ML initiatives and leverages AI tools, its core craft is cloud platform engineering, not direct AI/ML model development.

What you'd actually do

  1. Provide technical leadership and guidance to the cloud engineering team.
  2. Lead the design and development of secure, scalable, and reliable cloud infrastructure and platform tools.
  3. Drive adoption of modern DevEx (Developer Experience) practices and evolve CI/CD and developer tooling to improve delivery speed, quality, and consistency.
  4. Align platform strategy and roadmaps with business priorities; lead cross-functional initiatives to modernize SDLC practices.
  5. Implement real-time telemetry pipelines and workflows for large-scale platform observability and analytics.

Skills

Required

  • 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.

Nice to have

  • 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 for operational efficiency.
  • Published contributions to open-source or industry-recognized projects.
  • Hands-on experience building AI agents and MCP servers/integrations at scale using frameworks such as Google ADK, Anthropic SDKs, and standard agent orchestration tooling.
  • Experience with enhancing AI-powered coding ecosystems with enterprise specific tooling to improve developer productivity and platform engineering workflows.

What the JD emphasized

  • Hands-on experience building AI agents and MCP servers/integrations at scale using frameworks such as Google ADK, Anthropic SDKs, and standard agent orchestration tooling.
  • 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.