Senior Lead Software Engineer Cloud Platforms
About The Position
As a Senior Lead Software Engineer, Cloud Platform, within JPMorgan Chase’s Corporate Sector AI and Machine Learning Data Platforms team, you will design and deliver secure, high-quality technology solutions that support the firm’s data and analytics strategy. You will develop cloud-based products, enhance productivity, and enable responsible innovation across the firm, working with artificial intelligence and machine learning to support business success in a collaborative environment. The role provides technical leadership for cloud engineering and guides the design and development of secure, scalable, reliable cloud infrastructure and platform tools. It focuses on improving developer experience through modern practices, CI/CD, developer tooling, paved paths, and self-service workflows. You will align platform strategy with business priorities, modernize SDLC practices, govern strategic tooling, and partner with development teams to address platform bottlenecks. The role also supports platform observability through real-time telemetry, promotes developer productivity through documentation and training, and advances AI-assisted coding and AI-powered development ecosystems. You may contribute to AI agents and Model Context Protocol integrations using frameworks such as Google ADK and Anthropic SDKs.
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 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 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 AI-assisted coding tools and AI-powered development ecosystems to accelerate workflows, code generation, and engineering productivity.
- Contribute to the design and development of AI agents and Model Context Protocol integrations using frameworks such as Google ADK and Anthropic SDKs and related tooling.
Benefits
- Competitive total rewards package, including base salary and, for eligible roles, commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
- Comprehensive health care coverage.
- On-site health and wellness centers.
- Retirement savings plan.
- Backup childcare.
- Tuition reimbursement.
- Mental health support.
- Financial coaching.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
