Sr Lead Software Engineer

• Design and build AI-augmented migration tooling, using Claude Code and Copilot, that automates discovery, code transformation, containerisation, and validation across compute platforms.
• Engineer agentic workflows that analyse legacy workloads, generate migration artefacts (Dockerfiles, Helm/Kubernetes manifests, CI/CD pipeline definitions), and produce reviewable pull requests against real codebases.
• Build the guardrails: automated validation, rollback, and continuous verification so AI-generated migration changes are safe to ship at scale.
• Establish reusable patterns, prompts, evals, and reference implementations that let the rest of the migration org apply these tools consistently and reliably.
• Partner closely with the platform engineering teams that build and operate GKP, GCS, Gaia VSI and the container golden path, so the tooling targets the correct end state.
• Work directly with the migration execution and enablement teams to understand real blockers, then encode the solutions into tooling rather than one-off fixes.
• Measure and improve the quality, cost, and throughput of AI-driven migration - treating model output quality and human-review load as engineering metrics to optimise.
• Contribute to the firm's practice for safe, effective use of agentic coding tools on production codebases.

Attributes of Engineers in the Platform Migration group

• A builder's bias: you ship tools that other engineers depend on, and you measure success by migrations completed, not demos given.
• Comfort at the frontier: you are energised, not intimidated, by fast-moving AI tooling and are willing to establish practice where none exists yet.
• Healthy scepticism: you trust automated output only as far as your validation proves it, and you build the checks accordingly.
• Optimism and adaptability when faced with legacy complexity, coupled with the drive to solve hard problems and continuously optimise.
• Respect for people and opinions, and the confidence to offer your point of view.
• Dedication to continuous improvement of your own skillset and of the tools around you.
• A strong personal identification with the firm's values.

• Strong software engineering fundamentals and hands-on delivery in Python, Go, or Java.
• Practical, production-grade use of AI coding assistants - Claude Code, GitHub Copilot, or equivalent agentic tooling - to build and ship real software, not just autocomplete.
• Building automation and tooling that operates on real codebases: code parsing/transformation, templating, and generating change as reviewable pull requests.
• Cloud-native platforms and their primitives: Kubernetes, containers (Docker/OCI), and at least one of AWS, GCP, or Cloud Foundry / VCF.
• CI/CD and automated deployment pipelines.
• Designing validation and guardrails for automated change, testing, verification, and safe rollback.
• End-to-end application infrastructure concerns such as authentication/authorization and systems integration.
• A consultative, problem-solving approach and the ability to communicate technical concepts clearly.
• Excellent written and spoken communication skills.
• Bachelor's degree in Computer Science, Computer Engineering, or a related field of study, plus working experience in a role such as Software Engineer, Application Developer, or related occupation.

Preferred qualifications, capabilities, and skills

• Experience building on top of LLM APIs: agent frameworks, tool/function calling, retrieval, and writing evals to measure output quality.
• Prompt and context engineering as an applied discipline, including cost/latency/quality trade-offs.
• Container build and supply-chain tooling: Dockerfiles, buildpacks/Kaniko, SBOM, image signing, hardened base images.
• Infrastructure-as-code tools such as HashiCorp Terraform.
• Static analysis, AST-level code transformation, or compiler/language-tooling experience.
• Migration or modernisation programmes at scale, and proficiency managing large infrastructure deployments (compute, container systems, storage, networking).
• Global financial services and regulatory / compliance considerations relevant to workload deployment.
• Database and messaging technologies such as MySQL, Cassandra, Kafka, CockroachDB, or Oracle.

You'll be building at the leading edge of AI-assisted software engineering, on a problem with real scale and real impact - modernising the firm's compute estate - where the tools you build are used every day by the teams migrating it. Besides being in a strong team, we thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver products that help our clients succeed.

• Hands-on, daily work with frontier AI coding tools, and a mandate to define how the firm uses them.
• Continued career advancement opportunities, including industry-recognised certifications such as AWS and CKAD.
• Exposure to strong mentorship and leadership examples.
• Professional and technical development programs.
• Membership of a close-knit, collaborative, diverse team that encourages networking.

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives., Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.