Lead Software Engineer (Commercial & Investment Bank - Digital & Platform Services)

Lead Software EngineerWe have an exciting and rewarding opportunity for you to take your software engineering career to the next level.As a Lead Software Engineer at JPMorganChase within the Commercial & Investment Bank - Digital & Platform Services, you provide technical leadership and strategic direction for one or more agile teams delivering trusted, market-leading technology products in a secure, stable, and scalable way. You drive architectural decisions, set engineering standards, and mentor engineers while remaining hands-on with critical technology solutions that support the firm's business objectives.Job ResponsibilitiesExecutes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problemsDevelops secure high-quality production code, and reviews and debugs code written by othersDrives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.Leads technical design and architecture for complex, cross-functional systems, establishing patterns and standards that teams adopt at scale; Drives software solutions from concept through delivery, resolving ambiguous and novel technical challenges that span multiple domains and business functionsArchitects secure, high-quality production systems and oversees algorithmic design ensuring performance, reliability, and maintainability across distributed environments; Champions and governs the adoption of enterprise-authorized AI coding tools across the team; defines best practices for AI-assisted development (code generation, refactoring, test automation, documentation), establishes validation frameworks through peer review and automated testing, and drives measurable improvements in delivery velocity and code qualityShapes the team's SDLC toolchain strategy, identifying and implementing AI-assisted development and automation capabilities that maximize engineering throughput and reduce toilOwns architecture and design artifacts for complex, enterprise-scale applications; ensures design constraints, non-functional requirements, and security standards are met across all team deliverables; Synthesizes insights from large, diverse data sets to drive continuous improvement in system architecture, application performance, and engineering processes; presents findings and recommendations to senior leadershipIdentifies systemic technical debt, hidden failure patterns, and architectural risks; develops and prioritizes remediation roadmaps that improve coding hygiene and platform resilienceMentors and coaches engineers at all levels, conducting design reviews, driving technical upskilling, and fostering a culture of engineering excellenceLeads software engineering communities of practice; evaluates emerging technologies and makes build/buy/adopt recommendations to engineering leadership; Partners with product owners, architects, and business stakeholders to translate business strategy into technical roadmaps and execution plansRequired Qualifications, Capabilities, and SkillsFormal training or certification on software engineering concepts and 5+ years applied experienceHands-on practical experience delivering system design, application development, testing, and operational stabilityDemonstrated experience leading effective use of approved AI-assisted software development tools (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 engineers on safe, compliant adoption within delivery practicesProven track record of leading AI-assisted software development adoption within engineering teams, including establishing governance frameworks, validation standards, and reusable patterns; demonstrated ability to critically evaluate AI-generated outputs for correctness, performance, security, and architectural fit; Deep understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to define team-wide policies and coach engineers on safe and effective AI tool usageExpert-level IBM iSeries (AS/400) development experience; DB2 for i — files, views, indexes, triggers, stored procedures, performance optimization, and capacity planningLANSA / Visual LANSA IDE development with experience leading LANSA upgrade planning, execution, and migration strategies across environments; IBM MQ and CDC Replication (InfoSphere CDC / IIDR or equivalent) — architecture, implementation, and troubleshooting at scaleJava & Python on IBM i (PASE environment) with the ability to define integration patterns and coach team membersAdvanced debugging and root cause analysis — STRDBG, STRISDB, Service Entry Points, job logs, Visual Explain, remote Java/Python debug; ability to lead production incident triageSustained resiliency & maintenance leadership — HA/DR strategy and failover testing, PTF management, performance tuning, and technical debt remediation roadmapsGit version control (Bitbucket/GitHub), Aldon LMI, Robot Scheduling, ServiceNow — with experience defining branching strategies and release workflows; AI-powered tools — GitHub Copilot, ChatGPT, Claude agents; advanced prompt engineering for legacy code analysis, modernization assessment, and documentation generationPreferred Qualifications, Capabilities, and SkillsExpert proficiency in CLP, CLLE, RPGLE, SQLRPGLE, LANSA, Visual LANSA IDE development (free-format preferred) with demonstrated ability to set coding standards and conduct architecture reviewsDeep knowledge of ILE concepts, service programs, and modular application design; experience leading modernization efforts including web services (REST/SOAP) from IBM i or Python/JavaMastery of data areas, data queues, and inter-process communication on IBM i; experience designing event-driven and asynchronous processing architecturesFamiliarity with IBM i Access Client Solutions (ACS), Navigator, and IBM Rational Developer for i (RDi) or VS Code with Code for IBM i extension — with ability to standardize team development environments;Hands-on experience with HA/DR tools (e.g., MIMIX, iTera, Quick-EDD, or IBM PowerHA) including DR runbook ownership and failover drill execution; ITIL foundation knowledge for service management and change advisory processes; experience representing engineering in CAB reviews