Engineering Manager

You will lead a team of 8–12 engineers and be accountable for hiring, growth, performance, retention, and delivery. You will also help the team adopt Brandt's engineering standards and improve how it plans, builds, and ships software.

The Brandt Operating Model defines how our teams work; within it, you decide how your team applies the model: the planning rhythm, the review practices, and where AI belongs in the workflow. You own the hiring decision for your team inside our structured process. The model itself is continuously improving, and the Engineering Managers are central to shaping it. When part of it does not fit your team, bring the evidence to your peers and make the case for changing it.

You also own the structural health of your team's technology. Maintain and manage your team’s technical debt backlog in tandem with the Tech Leads. You put upkeep in the plan beside feature work, make the cost of pushing it out visible, and escalate when commitments would push it out again.

Technical leadership is a partnership. Tech leads report to the Chief Engineer, who owns the technical craft line and the company-wide standards. You contribute to your tech lead's review and help shape the standards your team adopts.

Success means a team that ships valuable work predictably, owns quality, develops its people, and improves velocity without trading away reliability.

We use AI throughout planning, development, testing, and delivery. Engineers remain accountable for what reaches an agency and its customers.

As a manager, you will use the same tools well enough to judge where they help and where they create risk. You will turn lessons from your team into better company practices. Delivery metrics come from our tooling, and we use them to improve the work, not rank individuals.

Experiment freely with how your team works inside the operating model. We hold a higher bar for what reaches an agency, where the cost of a mistake lands on someone's trip or license. When something goes wrong, we look for the cause before we add a checkpoint.

Build a reliable delivery record by planning in small batches, surfacing risk early, and renegotiating scope before dates slip.

Design how your team verifies its work, so review and testing keep pace with what the team can now produce.

Decide where AI belongs in your team's workflow, starting with the simplest approach that solves the problem.

Maintain the people-management basics: regular 1:1s, timely feedback, clear development plans, and fair handling of performance concerns.

Hire through our structured process, elevating your team by making great hiring decisions.

Adopt Brandt's delivery standards and work with the Chief Engineer to improve them based on your team's experience.

Hold engineers accountable for quality.

Sponsor engineers for promotions, earned specialties, and stretch roles.

Improve delivery metrics on your published scorecard, and tell us when a metric stops describing reality.

Have led a team near this size while owning both people management and delivery commitments.

Have found the real constraint in a delivery system, can explain how you knew, and can name a time you were wrong about it.

Have paid down deferred maintenance while still shipping, and can show what got better.

Have changed how a team works and can explain the results, tradeoffs, and anything that got worse.

Have hands-on experience with agentic development workflows, have evidence from your own team of where AI helps and where it does not, and can describe catching plausible but incorrect AI-generated work and what you changed afterward.

Have changed your mind in the last year about where AI belongs in engineering work, and can say what moved you.

Write things people can act on without a meeting, give timely feedback, and have actively sponsored someone's growth.

Make commitments carefully and communicate risks early.

Leading teams through a delivery-model change, such as an agile transformation, platform migration, or shift from QA-owned to engineer-owned quality.

Working across more than one product domain or business line.

Working with regulated, procurement-driven, or public-sector customers, where "move fast" meets contract language.

We do not use years of experience or degrees as proxies for ability. We care about evidence of the behaviors above. If you can show most, but not all, of them, we would still like to hear from you.

You will be measured on team-level delivery throughput, quality and reliability metrics, hiring outcomes, and the retention and growth of your engineers. We do not use per-engineer output counts or AI-usage statistics as performance measures.

This is a transformation, not a maintenance role. You will inherit legacy code, uneven practices, fixed deadlines tied to hunting seasons and contracts, and some change fatigue. This job is for someone who wants to build the system, not operate a settled one.