Lead Software Engineer, Cloud Platforms

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 160,000 - 260,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Software Engineer, Cloud Platform in Jersey City, NJ. Build secure, scalable cloud infrastructure and AI-enabled data platforms, guiding DevEx and developer tooling adoption across the enterprise.

You will drive modern SDLC practices, collaborate with cross-functional teams, and lead initiatives to improve delivery speed, reliability, and governance in a fast-paced, innovative environment.

Qualifications

• 5+ years of software engineering experience with cloud platforms.
• Experience with at least one major cloud provider (AWS, Azure, or GCP).
• Strong knowledge of containerization and orchestration (Docker, Kubernetes, ECS, etc.).
• Expertise in DevEx and CI/CD tooling (Jenkins, Spinnaker, Bitbucket, GitHub).
• Cloud security best practices and DevSecOps processes.
• Programming proficiency in Golang or Python.

Responsibilities

• Provide technical leadership to the cloud engineering team.
• Lead design/development of secure, scalable cloud infrastructure and platform tools.
• Advise on modern DevEx practices and CI/CD tooling adoption.
• Align platform roadmaps with business priorities and modernize SDLC.
• Evaluate and govern strategic tooling to improve developer experience.
• Collaborate to identify and eliminate platform bottlenecks.
• Define paved paths and self-service workflows for developers.
• Implement real-time telemetry pipelines for observability.

Skills

Cloud platforms experience

DevSecOps

AI/LLM tooling

Prompt engineering

Golang/Python

CI/CD practices

Security best practices

Education

Master's degree in a related field

Tools

Docker

Kubernetes

ECS

Terraform

Crossplane

Jenkins

Spinnaker

Bitbucket

GitHub

Splunk

Grafana

Datadog

Prometheus

Job description

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, you’ll 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 Lead Software Engineer, Cloud Platform at JPMorgan Chase within the Corporate Sector 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. You’ll work with us to develop cloud-based products, enhance productivity, and enable responsible innovation across the firm. Together, we’ll harness the power of artificial intelligence and machine learning to create new opportunities and drive business success. You’ll 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 topofGoogle 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

• 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/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.