Senior Lead Software Engineer, Cloud Platforms

Are you ready to shape the future of technology at a global financial leader Join us and make a real impact by building advanced cloud platforms that power data-driven decision making. At JPMorgan Chase youll collaborate with top talent leverage cutting-edge tools and help deliver solutions that transform how we work. This is your chance to push boundaries grow your expertise and be part of a team that values innovation and continuous learning. Discover a career adventure where your ideas matter and your skills drive change.

As a Senior Lead Software Engineer Cloud Platform at JPMorgan Chase in the Corporate AI and Machine Learning Data Platforms team you will play a key role in designing and delivering secure high-quality technology solutions that support our data and analytics strategy. Youll work with us to develop cloud-based products enhance productivity and enable responsible innovation across the firm. Together well harness the power of artificial intelligence and machine learning to create new opportunities and drive business success. Youll have the chance to collaborate lead and grow in a dynamic inclusive environment.

Job 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 ofAI-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 ofGoogle ADK Anthropic SDKs etc. and related tooling to enable intelligent scalable platform automation.

Required Qualifications Capabilities and Skills

• Formal training or certification on software engineering concepts and 5 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.

Preferred Qualifications Capabilities and Skills

• Masters 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.