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.

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 ...