Cloud Platform Engineer Lead - AI & DevEx

JPMorgan Chase

Palo Alto (CA)

On-site

USD 204,000 - 285,000

Full time

14 days+

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Job summary

JPMorgan Chase is seeking a Principal Software Engineer to lead cloud platform engineering within the Chief Data and Analytics Office's Data Platforms division. You will shape technical direction, build secure, scalable cloud solutions, and drive AI/ML-enabled initiatives with cross-functional teams.

The role emphasizes DevEx, CI/CD modernization, and innovative tooling, including AI-assisted coding, MCP integrations, and scalable automation.

Qualifications

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.

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.