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Lead Software Engineer - Application Owner & Release Manager

J.P. Morgan
Glasgow, GBR
Full-time
Senior
Onsite
Discovered 2 weeks ago
PythonJavaDatabricksAmazon Web Services
Free

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Job responsibilities

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

Required qualifications, capabilities, and skills

  • Bachelor’s degree or equivalent practical experience
  • Hands-on experience delivering system design, application development, testing, and operational stability in an agile environment
  • Proficiency in Python and Java
  • Proficiency in automation and continuous delivery methods, including continuous integration and continuous deployment practices
  • Working knowledge of cloud-native delivery on Amazon Web Services (for example: object storage, compute, containers, and managed data processing services)
  • Understanding of technology risk, controls, and compliance concepts, including identity and access management and audit readiness
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (for example: coding, code review, test acceleration, troubleshooting), including setting expectations to validate AI outputs for correctness, performance, and security
  • 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; ability to coach engineers on safe, compliant adoption within delivery practices
  • Ability to understand an application end-to-end, including dependencies, data flows, and deployment topology
  • Strong organization, prioritization, and communication skills, with the ability to influence partners without direct authority
  • Comfort operating in ambiguity and translating broad mandates into an actionable backlog
  • Experience serving as an application owner, site reliability engineer, production management lead, or technology risk and controls partner in a regulated environment
  • Familiarity with Databricks and cloud data-lake patterns using object storage as a core data store
  • Experience driving remediation of security findings and coordinating coordinated upgrades across frameworks, runtimes, and infrastructure-as-code
  • Understanding of resiliency concepts such as recovery time objectives, recovery point objectives, multi-zone design, and disaster recovery testing
  • Experience partnering with data science teams and business stakeholders to translate analytical needs into governed, compliant technology solutions
  • Exposure to using AI-assisted tooling to reduce operational toil while retaining strong human judgment and accountability
  • Domain awareness of wholesale or commercial credit risk analytics and modernization from monoliths to microservices

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