Key Responsibilities of the Role
- 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.
Required qualifications, capabilities, and skills
- 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.
What's in it for you?
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.
Skills Required
- 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)
- Building automation and tooling that operates on real codebases: code parsing, transformation, templating, generating reviewable pull requests
- Cloud-native platforms and 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
- Consultative problem-solving approach with strong written and spoken communication skills
- Bachelor's degree in Computer Science, Computer Engineering, or related field plus relevant software engineering experience
- Experience building on top of LLM APIs, agent frameworks, tool/function calling, retrieval, and writing evals
- Prompt and context engineering, 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
- Experience with migration/modernisation programmes at scale and large infrastructure deployments
- Experience or knowledge of global financial services, regulatory/compliance considerations
- Familiarity with databases and messaging: MySQL, Cassandra, Kafka, CockroachDB, or Oracle
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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