Engineering Lead

Engineering Lead

Large, Complex Federal Government Program | Full-Time W-2 | Fully Remote (U.S.)

The Problem We're Hiring You to Solve

Monthly production releases. Zero escaped critical defects. Most engineering organizations treat those as a tradeoff. On this program they are both commitments, measured every release, in front of the customer.

We are hiring the engineering leader who builds an organization that delivers both at once: multiple cross-functional development teams modernizing a federal home loan benefit platform while sustaining the 20-year-old system it replaces. If you believe speed and quality are the same discipline practiced well, and you have the delivery record to prove it, keep reading.

The Opportunity

Most engineering leadership roles ask you to protect a delivery machine someone else built. This one asks you to build the machine.

The program spans multiple development teams working in parallel across a modern platform (Salesforce-centered, configuration-first, supplemented by serverless capabilities in a government cloud) and a legacy suite that must stay stable until it is decommissioned. Work arrives through a formal intake process that turns business needs into executable plans with committed scope, timelines, and team sizing in days. Then your organization delivers against those commitments, publicly and measurably.

The quality bar is unusually explicit. Every release ships with 100% automated test coverage for its features before user acceptance testing begins. Defect detection before UAT must exceed 95%. Escaped critical defects must be zero. Critical production bugs get fixed in three days. Accessibility and security compliance are release gates, not aspirations. These are not stretch goals on a slide. They are how the program measures the engineering organization every month.

That bar is exactly why this role is interesting. Hitting it once takes heroics. Hitting it every month takes an engineering system: disciplined definition of done, test automation as a first-class craft, engineers who own quality instead of throwing code over a wall, and a leader who builds all of that into how teams work rather than inspecting it in afterward. That leader is you.

You will work alongside a Senior DevSecOps & Platform Engineering Lead who owns the delivery pipeline and an Enterprise Solution Architect who owns the designs. You own the organization that turns those designs into shipped, tested, production software.

What You'll Own

• The engineering organization. Lead multiple cross-functional development teams across modern and legacy platforms, flexing team size and composition as workflows through intake. Teams form, deliver, and re-form around the work. You make that fluid instead of chaotic.
• Delivery you put your name on. Commit to scope, level of effort, and timelines in executable plans, then hit them. When you cannot, say so early, with a recovery plan, before the customer discovers it.
• A quality system, not a QA gate. Engineer quality into how teams work: definition of done that includes full automated testing, code review that catches problems, and metrics that surface risk early. The outcomes that prove it: zero escaped critical defects, defect detection above 95% before UAT, and critical fixes inside three days.
• Test automation as a craft. Build the discipline where every feature ships with complete positive and negative automated coverage, and the regression suite becomes the safety net the customer trusts enough to focus UAT on new functionality only.
• The monthly release drumbeat. Production value ships every 30 days or faster, release after release, without burning the team down to do it.
• Dual-stack engineering. Run modern configuration-first platform development and legacy sustainment side by side, including the warranty on everything your teams release.
• Engineering standards that outlast you. Set and enforce the bar for code quality, review, documentation, and definition of done across every team, and keep documentation current with every release because the program requires it and good engineering does too.
• AI-native development at team scale. Make AI-assisted engineering the norm across your organization, not the hobby of your three most curious engineers, while holding AI-assisted work to the same zero-escaped-defect bar as everything else.
• The talent engine. Hire deliberately, grow engineers visibly, retain the strong ones, and raise the bar with every addition.

AI-Native Engineering at Team Scale

AI is part of how PhoenixTeam works. Plenty of leaders can use AI tools themselves. This role is about something harder: making an entire engineering organization genuinely better with them.

We are looking for someone who already uses tools like Claude Code, Cursor, or GitHub Copilot in their own work, and who has begun leading teams through the shift: establishing standards for responsible AI-assisted development, using AI to expand automated test coverage and accelerate code review, applying it to defect analysis and documentation, and measuring whether it actually improved throughput and quality rather than assuming it did.

The accountability question matters most in a federal environment with a zero-escaped-critical-defect standard. AI-generated code is your teams' code. It gets the same review, the same testing, and the same ownership as anything an engineer typed by hand. You set that culture.

Boundaries are non-negotiable: federal environments govern what tools may touch government code, systems, and data. Use AI wherever it creates leverage, and understand the security, data, privacy, and authorization boundaries governing where and how it can be used.

Tools will change. The leadership behavior we are hiring for will not: continually ask where your organization's engineering hours are going and eliminate the waste responsibly.

What Great Looks Like

Twelve months in, we would expect to see:

1. The cadence held. Production value shipped at least monthly, every month, with zero escaped critical defects and a team that is energized rather than exhausted.
2. The regression suite earned trust. Automated coverage is complete enough that UAT focuses on new features, and the customer stopped asking whether old functionality still works.
3. Quality metrics are boring in the best way. Detection rates above 95%, critical fixes inside three days, and defect trends the customer reviews without concern.
4. Teams flex without drama. Work moves from intake to a staffed, productive team quickly, and re-forming teams around new work stopped being disruptive.
5. AI lifted the organization measurably. Throughput and coverage improved with AI-assisted engineering, defect rates did not, and your standards for responsible use became the program's standards.
6. Both stacks are healthy. Legacy sustainment is quiet and predictable while modern platform velocity grows quarter over quarter.
7. The bench is stronger. Engineers you hired and grew are visibly better, your leads lead, and departures are rare and regretted.
8. The customer asks for more. Delivery confidence earned the program expanded scope.

What You Bring

We care about evidence more than resumes. Expect us to ask what your organizations shipped, what your defect and delivery metrics actually were, how you turned around a team that was missing its commitments, and how AI functions across your teams today.

• A multi-team delivery record. You have led engineering organizations of multiple teams building and shipping production software, and you can walk us through the delivery and quality outcomes with numbers.
• Hands-on credibility. You still read code, review designs, and go deep when it matters. Engineers respect your technical judgment, not just your title.
• A quality system you built. You have taken an organization to measurably low defect escape rates through engineering discipline and test automation, not through more manual QA at the end.
• Federal delivery experience. You have shipped software inside a regulated federal environment and treat security, accessibility, authorization, and documentation requirements as delivery constraints to engineer within, not excuses for slipping.
• Metrics fluency. You run engineerin