Lead Software Engineer, Cloud Platforms
About The Position
As a Lead Software Engineer on JPMorgan Chase’s Corporate Sector AI and Machine Learning Data Platforms team, you will design and deliver secure, high-quality technology solutions supporting the firm’s data and analytics strategy. You will develop cloud-based products, enhance productivity, and enable responsible innovation. The role provides technical leadership for cloud engineering, including development of secure, scalable, reliable infrastructure and platform tools. You will advance developer experience, CI/CD, developer tooling, and modern SDLC practices; align platform strategy with business priorities; and work with development teams to remove bottlenecks and enable self-service workflows. You will also build observability capabilities and promote adoption of AI-assisted development tools, AI agents, and Model Context Protocol integrations. JPMorgan Chase offers a competitive total rewards package, with salary based on role, experience, skill set, and location. Eligible roles may include commission-based pay and/or discretionary incentive compensation. Benefits are eligibility-dependent and include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, and financial coaching. Additional compensation and benefits details are provided during the hiring process.
Requirements
- Formal training or certification in software engineering concepts and at least 5 years of applied experience.
- Hands-on experience with at least one major cloud provider: AWS, Azure, or GCP.
- Advanced knowledge of containerization and orchestration platforms such as Docker, Kubernetes, or ECS.
- Demonstrated expertise in developer experience and CI/CD tools such as Jenkins, Spinnaker, Bitbucket, or GitHub.
- Strong knowledge of cloud security best practices, shift-left methodologies, and DevSecOps processes.
- Strong programming skills in Golang or Python and a solid understanding of software development best practices.
- Proficiency with cloud infrastructure provisioning tools such as Terraform, KRO, or Crossplane.
- Experience with logging and monitoring tools such as Splunk, Grafana, Datadog, or Prometheus.
- Deep understanding of cloud infrastructure design, architecture, and migration strategies.
- Demonstrated proficiency with AI-assisted coding workflows, including LLM-powered development tools, spec-driven development methodologies, and prompt engineering for software engineering use cases.
Nice To Haves
- 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 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 or integrations at scale using frameworks such as Google ADK, Anthropic SDKs, and standard agent orchestration tooling.
- Experience enhancing AI-powered coding ecosystems with enterprise-specific tooling to improve developer productivity and platform engineering workflows.
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 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 and 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 platform bottlenecks.
- 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.
- Promote developer productivity tools through documentation, training, office hours, and engagement with the developer community.
- Standardize the use of AI-assisted coding tools and AI-powered development ecosystems to accelerate workflows, code generation, and engineering productivity.
- Contribute to designing and developing AI agents and Model Context Protocol integrations using frameworks such as Google ADK and Anthropic SDKs.
Benefits
- Comprehensive health care coverage
- On-site health and wellness centers
- Retirement savings plan
- Backup childcare
- Tuition reimbursement
- Mental health support
- Financial coaching
- Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
