Technical Delivery Manager, Engineering & Consulting
About Legence Legence (Nasdaq: LGN) is a leading provider of engineering, consulting, installation, and maintenance services for mission-critical systems in buildings. The company specializes in designing, fabricating, and installing complex HVAC, process piping, and other mechanical, electrical, and plumbing (MEP) systems—enhancing energy efficiency, reliability, and sustainability in new and existing facilities. Legence also delivers long-term performance through strategic upgrades and holistic solutions. Serving some of the world’s most technically demanding sectors, Legence counts over 60% of the Nasdaq-100 Index among its clients.
Technical Delivery Manager, Engineering & Consulting Location: Any Legence location, with remote option Employment Type: Full-Time
About the Role Legence is seeking a Technical Delivery Manager who leads by building. This is a player- coach role in the fullest sense: you'll spend real time in the codebase — designing solutions, writing code, reviewing pull requests, and shipping — while leading a team of engineers and serving as the trusted technical voice for business stakeholders. You keep delivery on track not by administering process, but by understanding the work deeply enough to make the right calls, grow your team, and jump in yourself when it matters. The ideal candidate can present a solution approach to executives in the morning and implement a tricky integration in the afternoon. Deep, practical experience with AI-driven software development and enterprise systems is a must. What You'll Do
- Build and Ship
◦ Design and implement solutions hands-on: services, integrations, automation, and prototypes — you write production code, not just review it ◦ Own technical decisions on your initiatives: architecture, build-vs-buy, tooling, and integration approach ◦ Set the technical bar through code reviews, pairing, and example — engineers should learn from working alongside you ◦ Lead AI-driven development in practice: build with AI coding assistants and agentic workflows (e.g., Claude Code, GitHub Copilot), integrate LLM APIs into products and internal tools, and show the team how to get real leverage from these tools safely ◦ Ensure solutions integrate cleanly with enterprise systems — ERP/CRM, identity, data platforms, cloud infrastructure — and hold up on security, scalability, and maintainability
- Lead the Technical Team
◦ Lead a team of engineers day to day: set direction, assign ownership, and keep the team focused on the highest-value work ◦ Grow engineers through hands-on mentorship — pairing, design discussions, and honest, specific feedback rather than annual-review platitudes ◦ Build a strong engineering culture: high standards for code quality and testing, healthy debate on design, and shared ownership of outcomes ◦ Shape the team itself— participate in hiring, onboard new engineers, and develop senior engineers into technical leaders ◦ Shield the team from noise and churn; absorb ambiguity from stakeholders and hand engineers clear, well-framed problems ◦ Foster effective adoption ofAI development tools across the team, establishing shared practices for where they accelerate work and where human judgment stays in the loop
- Engage Stakeholders
◦ Act as the primary technical counterpart for business stakeholders and product owners ◦ Translate business goals directly into working solutions — shorten the distance between "what we need" and "here it is" with prototypes and demos rather than documents ◦ Communicate progress, risks, and trade-offs in plain language; earn trust by showing working software early and often ◦ Push back constructively when a request doesn't make technical or business sense, and bring better options
- Drive Delivery (Lightweight)
◦ Keep initiatives moving end to end — scope, sequence, ship — with just enough structure to stay predictable ◦ Remove blockers fast, usually by solving the underlying technical problem rather than escalating it ◦ Coordin