Python Technical Delivery Lead — Cloud Data Platforms (AWS/Databricks/Terraform)

J.P. MORGAN; Greater London; On-site; GBP 120,000 - 160,000; Full time

Job summary

J.P. Morgan is seeking a Senior Lead Software Engineer in London within the Credit data pond team under Wholesale credit risk technology.

You will guide AI-assisted engineering practices, define tooling standards, and drive secure, scalable software delivery across teams. The role emphasizes enterprise governance, code quality, and collaboration with a broad engineering community to deliver trusted market-leading technology products in a secure, stable, and scalable way.

Qualifications

• Formal training or certification on software engineering concepts with hands-on experience in system design and operational stability.
• Advanced in one or more programming languages.
• Experience establishing scalable operating models for enterprise AI-assisted development and governance.
• Experience setting validation expectations for AI outputs before merge/release.
• Experience using enterprise-authorized AI-assisted development tools for coding, review, and testing.

Responsibilities

• Provide technical guidance to the business and technical teams, contractors, and vendors.
• Develop secure, high-quality production code and review others' code.
• Drive adoption of AI-assisted engineering practices with measurable validation standards and automation across the SDLC/TLM toolchain.
• Define enterprise toolchain strategy and target-state architecture across planning, source control, build, test, security, deployment, and observability.
• Establish governance for automation-at-scale with guardrails and reusable templates.

Skills

Python

AI governance

Secure coding

Code review

Cloud native

Git

Tools

Git

CI/CD tooling

Job description

Job Description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorganChase within the Credit data pond team housed within Wholesale credit risk technology you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Establishes an enterprise-aligned operating model for AI-assisted engineering across teams (approved use cases, guardrails, RACI, auditability), ensuring consistent adoption that improves throughput and quality without increasing risk.
• Defines and enforces measurable validation standards for AI-assisted changes (mandatory peer review, secure coding controls, automated test thresholds, performance/regression checks, release readiness criteria) and embeds them into CI/CD quality gates.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
• Sets the enterprise toolchain strategy and target-state architecture across planning, source control, build, test, security, deployment, and observability—driving standardization and reducing fragmentation across teams.
• Establishes “automation-at-scale” governance (golden pipelines, shared libraries/templates, reference implementations, and platform guardrails) to accelerate delivery while maintaining resiliency and security expectations.
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and advanced applied experience in Python
  Hands‑on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s)
• Establishes a scalable operating model for enterprise-authorized AI-assisted development (approved use cases, guardrails, roles/approvals, auditability) and drives consistent adoption across multiple teams.
• Sets clear validation expectations for AI outputs before merge/release—mandatory peer review, secure coding checks, automated test coverage thresholds, and documented acceptance criteria for high-risk or customer-impacting changes.
• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls.
• Establishes and enforces responsible AI governance for engineering workflows (approved use cases, data classification rules, escalation paths, auditability), ensuring adoption aligns with enterprise policy and regulatory expectations.
• Defines secure handling standards for AI inputs/outputs—prohibiting sensitive data exposure, mandating redaction/minimization, controlling access via least privilege, and ensuring appropriate logging and retention practices.
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience

About Us

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.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success.

We are an equal opportunity employer and place a high value on diversity and inclusion at our company.

We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law.

We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

About The Team

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.