Senior Lead Software Engineer Cloud Platforms

JPMorganChase•Jersey City, NJ

About The Position

As a Senior Lead Software Engineer, Cloud Platform at JPMorgan Chase within the 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, working across teams to apply artificial intelligence and machine learning to business challenges.

Requirements

Formal training or certification in software engineering concepts and 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 tools that improve developer productivity through documentation, training, office hours, and engagement with the developer community.
Standardize AI-assisted coding tools and AI-powered development ecosystems to accelerate development 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, along with related tooling, for scalable platform automation.