Lead Software Engineer - Application Owner & Release Manager

JP Morgan Chase; Glasgow; On-site; GBP 62,000 - 102,000; Full time

Job summary

J.P. Morgan is seeking a skilled engineer to support Wholesale Credit Risk Technology Analytics in Glasgow. You will own governance, enable safe production changes, and drive resiliency initiatives within a regulated cloud-native environment.

The role requires hands-on design, development, testing, and CI/CD in an agile setting, with strong Python/Java skills and AWS expertise. Collaboration across teams is essential to manage risk and deliver secure software.

Qualifications

• We require a bachelor's degree or equivalent practical experience.
• We require hands-on experience delivering system design, application development, testing, and operational stability in an agile environment.
• We require proficiency in Python and Java.
• We require proficiency in automation and continuous delivery methods, including CI/CD.
• We require working knowledge of cloud-native delivery on AWS, with object storage, compute, containers, and data processing services.
• We require understanding of technology risk, controls, and compliance concepts.
• We require experience leading use of approved AI-assisted software development tools with validation for correctness, performance, and security.
• We require strong understanding of responsible AI use in engineering workflows, including data sensitivity and security.
• We require the ability to understand an application end-to-end, including data flows and deployment topology.
• We require strong organization, prioritization, and communication skills to influence partners.
• We require comfort operating in ambiguity and translating mandates into a backlog.

Responsibilities

• We own governance and records by maintaining system-of-record information and remediation workflows.
• We drive permit-to-operate activities by coordinating inputs and responses to production changes.
• We monitor risk findings, assess impact, and drive remediation with engineering teams.
• We approve access and control activities enforcing least privilege and periodic reviews.
• We own resiliency and recovery readiness with recovery plans and testing support.
• We manage technology lifecycle by identifying end-of-life components and coordinating upgrades.
• We lead firmwide initiatives by clarifying requirements and tracking completion.
• We lead release management aligning stakeholders and overseeing readiness and deployment.
• We develop secure, high-quality production code and contribute to reviews and improvements.
• We drive enterprise AI adoption to improve code quality, speed, and security with validated patterns.
• We apply lifecycle toolchain knowledge to increase automation value.

Skills

System design

Application development

Testing

Operational stability

Agile methodologies

Python

Java

CI/CD

AWS cloud

Risk & controls awareness

AI-assisted development tools

Responsible AI practices

End-to-end understanding

Communication & influence

Backlog management

Education

Bachelor's degree or equivalent practical experience

Tools

AWS

Databricks

AI-assisted development tools

Job description

Salary: £62,000 - 102,000 per year

Requirements

• We require a bachelors degree or equivalent practical experience.
• We require hands-on experience delivering system design, application development, testing, and operational stability in an agile environment.
• We require proficiency in Python and Java.
• We require proficiency in automation and continuous delivery methods, including continuous integration and continuous deployment practices.
• We require working knowledge of cloud-native delivery on Amazon Web Services, including object storage, compute, containers, and managed data processing services.
• We require understanding of technology risk, controls, and compliance concepts, including identity and access management and audit readiness.
• We require demonstrated experience leading effective use of approved AI-assisted software development tools, including setting expectations to validate AI outputs for correctness, performance, and security.
• We require strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations.
• We require the ability to understand an application end-to-end, including dependencies, data flows, and deployment topology.
• We require strong organization, prioritization, and communication skills, with the ability to influence partners without direct authority.
• We require comfort operating in ambiguity and translating broad mandates into an actionable backlog.

Responsibilities

• We own application governance and records by maintaining accurate system-of-record information, certifications, and remediation workflows.
• We drive permit-to-operate activities by coordinating required inputs, re-certifications, and stakeholder responses to move changes safely into production.
• We monitor and remediate risk findings by assessing impact, prioritizing actions with engineering teams, and driving closure within agreed timelines.
• We approve access and control activities by enforcing least privilege, segregation of duties, and periodic access reviews in partnership with control owners.
• We own resiliency and recovery readiness by maintaining recovery plans, supporting resiliency events, and partnering on testing and evidence collection.
• We manage technology lifecycle work by identifying end-of-life or prohibited components and coordinating upgrades across dependencies and teams.
• We lead firmwide initiatives and non-functional tasks by maintaining a consolidated view, clarifying requirements, and tracking completion.
• We lead release management by aligning stakeholders, managing dependencies and risk, and overseeing readiness, deployment, and post-release validation.
• We develop secure, high-quality production code and contribute to technical troubleshooting, reviews, and continuous improvement.
• We drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, while setting consistent validation standards and promoting reuse of effective patterns.
• We apply software development lifecycle toolchain knowledge, including enterprise-authorized AI-assisted development and automation capabilities, to increase the value realized through automation.

Technologies

• AI
• Cloud
• Support
• Java
• Marketing
• Python
• Security
• Web
• Databricks
• Machine Learning

More

We are J.P. Morgan, a global leader in financial services providing strategic advice and products to corporations, governments, wealthy individuals, and institutional investors. Our Corporate Functions teams span finance, risk, human resources, marketing, and other essential areas that help set our businesses, clients, customers, and employees up for success. We value inclusion, diversity, and equal opportunity, and we support reasonable accommodations for applicants and employees. This full-time role sits within our Wholesale Credit Risk Technology Analytics team and offers the opportunity to work across engineering, cyber, risk, resiliency, cloud, data, and software engineering in a highly regulated environment where we build trusted, long-term partnerships and deliver stable, scalable cloud-native analytics.

last updated 37 week of 2026