About this role
Summary/Objective Reporting to the Chief Information Officer, the IT Manager, Software Engineering is responsible for leading the firm’s software development function and modernizing delivery practices through the effective, secure, and governed use of technology. This role oversees the design, development, implementation, maintenance, and continuous improvement of custom and integrated software solutions, ensuring technology investments align with business priorities, regulatory expectations, security requirements, and long-term organizational strategy. Essential Functions Lead the full software development lifecycle for custom applications, integrations, automation, and data-enabled solutions that support organizational goals and user needs. Establish and manage modern AI-augmented development practices, including the responsible use of agentic AI tools for requirements analysis, prototyping, coding, testing, documentation, and delivery acceleration. Ensure all AI-assisted development activities operate within approved governance, security, privacy, compliance, architecture, and human-review standards. Plan and manage software project schedules, release plans, and enhancement backlogs. Manage, mentor, and develop a team of software developers, fostering strong engineering discipline, collaboration, continuous learning, and accountable delivery. Collaborate with business units, vendors, security, infrastructure, data, and leadership stakeholders to define requirements, prioritize work, evaluate solutions, and deliver measurable business value. Develop and execute strategies for application lifecycle management, including budgeting, resource planning, quality management, risk mitigation, platform modernization, and technology upgrades. Responsibilities & Duties Assign, prioritize, and track software development work across team members, vendors, and AI-assisted workflows to meet business commitments and support needs. Translate business needs into clear requirements, user stories, technical specifications, acceptance criteria, and delivery plans that can be effectively executed by developers and AI-enabled development tools. Oversee development standards for architecture, coding, source control, peer review, automated testing, release management, documentation, and production support. Evaluate, adopt, and govern agentic AI software development tools that can assist with code generation, refactoring, test creation, documentation, troubleshooting, and workflow automation. Maintain human-in-the-loop review processes to validate AI-generated outputs, prevent unmanaged technical debt, protect sensitive data, and ensure quality, security, and business alignment before release. Develop, execute, and manage robust testing practices, including unit testing, integration testing, regression testing, user acceptance testing, and AI-assisted test automation. Respond to and resolve application issues reported by users, monitoring tools, or production support teams, coordinating remediation and root-cause analysis as appropriate. Lead workstream planning, release readiness reviews, and recurring team meetings to discuss progress, risks, priorities, and delivery challenges. Partner with cybersecurity, compliance, and data governance stakeholders to ensure software solutions meet security, privacy, regulatory, and internal policy requirements. Oversee software updates, patches, dependency management, platform upgrades, and modernization efforts to improve functionality, maintainability, reliability, and security. Manage vendor relationships related to software development platforms, development tools, application vendors, implementation partners, licensing, support agreements, and contracted delivery resources. Track project, product, licensing, vendor, and operational budgets to ensure cost-effective use of resources for software development and application management. Research and assess emerging technologies, development platforms, AI engineering practices, automation opportunities, and software architecture patterns that may improve delivery speed, quality, or business capability. Maintain current documentation for software architecture, integrations, development standards, deployment processes, support procedures, AI tool usage, and operational runbooks. Organize training, coaching, and knowledge-sharing sessions to improve team skills in modern software engineering, secure coding, AI-assisted development, and business application support. Review software delivery metrics, system performance, production reliability, support trends, code quality indicators, and AI-development effectiveness to identify improvement opportunities. Prepare and present reports on software delivery status, product roadmaps, application health, AI adoption, risk items, and IT initiatives to senior management. This job description is not designed to cover or contain a comprehensive listing of essential functions or responsibilities that are required of the employee for this job. Essential functions and responsibilities and activities may change at any time with or without notice.