The Development Team Lead leads a team of software engineers building and maintaining Xactimate Desktop, a large, mature C#/.NET and WPF application. Reporting to the Software Development Manager, the Team Lead spends most of their time setting direction, developing people, removing obstacles, and ensuring the team delivers high-quality software predictably. They remain hands-on for roughly a third of their time, which keeps their technical judgment sharp and lets them model the practices they expect of the team. A central part of this role is leading the team’s adoption of AI-assisted development. The Team Lead champions practical, everyday use of AI coding tools, builds the habits and guardrails that make those tools effective on a large legacy codebase, and measures their impact on productivity and quality. Success requires strong technical depth, clear communication, and the ability to bring a team along through change. People Leadership • Lead, coach, and develop a team of software engineers through regular one-on-ones, clear expectations, and timely, actionable feedback. • Set individual and team goals, track progress with meaningful measures, and address performance concerns early and directly. • Hire engineers who raise the team’s capability by screening, interviewing, and making selection recommendations. • Build a team culture of ownership, trust, and continuous learning. AI Adoption & Productivity • Lead the team’s adoption of AI-assisted development tools (e.g., GitHub Copilot, Claude Code, or similar), moving the team from occasional use to consistent, effective daily practice. • Establish and refine AI-assisted workflows across the development lifecycle, including specification, design, implementation, code review, testing, and documentation. • Apply AI tooling to the specific challenges of a large legacy codebase: understanding unfamiliar code, expanding test coverage, refactoring safely, and accelerating modernization. • Define guardrails for responsible use, including review expectations for AI-generated changes, security and data-handling practices, and quality standards. • Measure the impact of AI tooling on throughput, cycle time, and quality, and share results and lessons learned with other teams and leadership. • Coach engineers individually on effective AI use and spread techniques that work across the team. Technical Leadership • Own code quality and adherence to department engineering standards for the team; review pull requests and ensure changes meet team standards. • Partner with principal engineers on architecture and technical direction so the team’s designs align with the broader product architecture. • Oversee technical planning so work is well understood, feasible, and appropriately sized before it begins. • Contribute hands-on (roughly 30% of time) through coding, code review, prototyping, and pairing, modeling best practices in testing and documentation. Delivery & Execution • Ensure the team meets its commitments and delivers high-quality software against agreed timelines and objectives. • Plan and prioritize work collaboratively with Product Management, negotiating trade-offs among scope, quality, and schedule. • Facilitate or participate in agile ceremonies (planning, stand-ups, reviews, retrospectives) and take part in the on-call rotation as required. • Surface delivery risks early and communicate them clearly, along with options for addressing them. Collaboration & Communication • Partner with the Software Development Manager and cross-functional leaders in Product, QA, and UX to improve processes and outcomes. • Coordinate cross-team engineering efforts, including shared architectural decisions, dependencies, and releases. • Engage with customers and internal stakeholders to gather feedback, communicate progress, and apply root-cause analysis to improve products and processes. • Present information clearly and credibly to both technical and non-technical audiences. Continuous Improvement • Identify and implement improvements to engineering workflows and agile practices. • Maintain accurate, current documentation of the team’s systems, practices, and decisions. • Stay current with evolving development tools and techniques, especially in AI-assisted engineering, and promote continuous learning on the team. Required Qualifications • 5+ years of professional software development experience with deep, hands-on technical proficiency. • Demonstrated ability (or strong aptitude) to lead software engineers, whether as a team lead or as a senior or technical lead who guided others’ work. • Strong experience with C#/.NET, and experience with WPF and MVVM or comparable desktop UI frameworks. • Familiarity with CI/CD tooling such as TeamCity. • A track record of delivering high-quality software on schedule while upholding engineering standards. • Fluency with agile methods (Scrum or Kanban) and iterative, incremental delivery. • Excellent written, verbal, and interpersonal communication skills. • Strong planning and organizational skills, with the ability to work independently and drive outcomes. • A product- and user-centered mindset in engineering decisions. • Coachability, openness to feedback, and a record of reliability. • Genuine curiosity about AI-assisted development and a willingness to lead others through changes in how they work. Preferred Qualifications • Hands-on experience using AI coding tools (e.g., GitHub Copilot, Claude Code, Cursor) in professional development work. • Experience introducing new tools or practices to a team and measuring their impact on productivity or quality. • Experience working in a large, long-lived codebase, including refactoring, improving test coverage, or modernization efforts. • Experience collaborating with distributed teams across time zones. • Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent experience. #LI-LM03 #LI-Hybrid