**Lead Software Engineer - Application Owner & Release Manager**
This senior role involves managing a critical cloud analytics platform's lifecycle and releases, ensuring resilience, security, and compliance. The position demands hands-on experience in delivering system design, application development, and operational stability using Python and Java in an agile environment. Key responsibilities include maintaining application governance, managing risk posture, and orchestrating safe releases into production. Proficient knowledge of AWS, cloud-native delivery, and technology risk controls is essential. influenci
Full Job Description
Location: GLASGOW, LANARKSHIRE, United Kingdom
Build solutions that matter in a highly regulated environment where resiliency and security are as important as innovation. Youll partner across engineering, cyber, risk, and resiliency to keep critical analytics platforms healthy and compliant while enabling teams to deliver change safely. This role offers breadth across cloud, data, and software engineering, plus the opportunity to lead through influence and strong execution. Youll help reduce toil through automation and create space for engineers and data scientists to do their best work. Join a team that values inclusion, growth, and pragmatic problem-solving.
As a Lead Software Engineer, Application Owner and Release Manager in the Wholesale Credit Risk Technology Analytics team, you will own day-to-day governance, risk posture, and operational resiliency for the Wholesale Credit Risk Analytics application estate. Youll keep the system-of-record accurate, guide work through firm controls, and ensure releases move to production safely with minimal disruption. Youll operate at the intersection of engineering, cyber, resiliency, and risktranslating firm-wide mandates into clear, executable actions for application teams. You dont need to write every line of code, but you understand the platform end-to-end and own outcomes. Youll partner closely with product owners, data scientists and machine learning engineers, site reliability engineering, and business stakeholders to deliver stable, scalable cloud-native analytics.
Job responsibilities
Own application governance and records by maintaining accurate system-of-record information, certifications, and remediation workflowsDrive permit-to-operate activities by coordinating required inputs, re-certifications, and stakeholder responses to move changes safely into productionMonitor and remediate risk findings by assessing impact, prioritizing actions with engineering teams, and driving closure within agreed timelinesApprove access and control activities by enforcing least privilege, segregation of duties, and periodic access reviews in partnership with control ownersOwn resiliency and recovery readiness by maintaining recovery plans, supporting resiliency events, and partnering on testing and evidence collectionManage technology lifecycle work by identifying end-of-life or prohibited components and coordinating upgrades across dependencies and teamsLead firmwide initiatives and non-functional tasks by maintaining a consolidated view, clarifying requirements, and tracking completionLead release management by aligning stakeholders, managing dependencies and risk, and overseeing readiness, deployment, and post-release validationDevelop secure, high-quality production code and contribute to technical troubleshooting, reviews, and continuous improvementDrive 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 patternsApply software development lifecycle toolchain knowledge, including enterprise-authorized AI-assisted development and automation capabilities, to increase the value realized through automationRequired qualifications, capabilities, and skills
Bachelors degree or equivalent practical experienceHands-on experience delivering system design, application development, testing, and operational stability in an agile environmentProficiency in Python and JavaProficiency in automation and continuous delivery methods, including continuous integration and continuous deployment practicesWorking 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 readinessDemonstrated 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 securityStrong 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 practicesAbility to understand an application end-to-end, including dependencies, data flows, and deployment topologyStrong organization, prioritization, and communication skills, with the ability to influence partners without direct authorityComfort operating in ambiguity and translating broad mandates into an actionable backlogPreferred qualifications, capabilities, and skills
Experience serving as an application owner, site reliability engineer, production management lead, or technology risk and controls partner in a regulated environmentFamiliarity with Databricks and cloud data-lake patterns using object storage as a core data storeExperience driving remediation of security findings and coordinating coordinated upgrades across frameworks, runtimes, and infrastructure-as-codeUnderstanding of resiliency concepts such as recovery time objectives, recovery point objectives, multi-zone design, and disaster recovery testingExperience partnering with data science teams and business stakeholders to translate analytical needs into governed, compliant technology solutionsExposure to using AI-assisted tooling to reduce operational toil while retaining strong human judgment and accountabilityDomain awareness of wholesale or commercial credit risk analytics and modernization from monoliths to microservices Own application health and releases, shaping secure cloud analytics that modernizes wholesale credit risk decisions. 
