Development Team Lead

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.

• 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.

• Lead the team’s adoption of AI-assisted development tools (e.g., Git Hub 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.

• 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.

• 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.

• 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…