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:
- 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.
- 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.
- 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.
- Teams flex without drama. Work moves from intake to a staffed, productive team quickly, and re-forming teams around new work stopped being disruptive.
- 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.
- Both stacks are healthy. Legacy sustainment is quiet and predictable while modern platform velocity grows quarter over quarter.
- The bench is stronger. Engineers you hired and grew are visibly better, your leads lead, and departures are rare and regretted.
- 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 engineering organizations on evidence: release cadence, defect detection and escape rates, cycle times, automation coverage, and you use those numbers to improve the system rather than to punish people.
- AI-forward leadership. You use AI engineering tools yourself and have led teams into using them well, with standards, measurement, and accountability.
- Customer-facing composure. You present delivery status, defend engineering decisions with evidence, deliver bad news early, and challenge unrealistic direction respectfully, including ours.
- Talent judgment. You hire well, grow engineers deliberately, and make hard calls about performance without outsourcing them to HR processes.
- U.S.-based, and able to obtain and maintain a federal Public Trust clearance.
We do not screen on degrees or year counts. If your evidence is strong, we want to talk.
Helpful, Not Required
- Salesforce delivery leadership, or leadership of teams on a comparable configuration-first enterprise platform.
- Deep background in test automation frameworks and strategy.
- Experience running legacy sustainment and modernization in parallel, or decommissioning a production system.
- Familiarity with 508 accessibility compliance in delivery.
- Mortgage or housing finance experience is not required. We will teach you the domain.
Leadership Expectations
This is an organizational leadership role with a hands-on soul.
You own outcomes across multiple teams, which means your leverage comes through leads, standards, and systems rather than personal output. But you stay close enough to the work to know when a design is wrong, an estimate is padded, or a team is quietly drowning. Engineers should experience you as a leader who understands what they do, because you can still do it.
You work directly with federal customers and decision-makers. You present delivery status with candor, defend your teams' engineering decisions with evidence, and challenge poor technical or program direction respectfully. Silent disagreement is a failure mode here, and so is shielding the customer from bad news until it becomes a crisis.
You develop the leaders under you deliberately, and you hold the engineering bar even when the schedule argues against it, because on this program the quality metrics are the schedule.
You'll Probably Love This Role If...
You are the leader whose teams ship on a rhythm others find implausible, and you can explain exactly which disciplines make it possible. You think a public, measured quality bar is a gift, because it settles arguments that consume other organizations. You would rather build a delivery machine than inherit one. You like customers in the room. And you are genuinely energized by leading engineers through the AI shift, because you have seen what it does for a team that adopts it seriously.
This May Not Be the Role for You If...
We would rather you self-select now than be unhappy in month three. You may struggle here if you:
- Lead from dashboards and status meetings, and stopped engaging with the actual engineering.
- Treat quality as the QA team's job rather than an engineering outcome you own.
- Negotiate quality bars down when schedules get tight.
- Hide delivery risk from customers until it becomes undeniable.
- Prefer stable, fixed teams and find flexing around the work disruptive.
- View AI as a novelty rather than an engineering capability your organization must master.
- Stopped learning when you became senior.
None of that makes someone a bad leader. It makes them a bad fit for this particular job.
Why PhoenixTeam
- We are practitioners, not a staffing shop. PhoenixTeam is a woman-owned small business founded and led by housing finance technologists who still do the work. Our teams have spent years embedded inside federal housing programs, from loan guaranty to rural housing lending to mortgage insurance. You will build your organization alongside leaders who have shipped, not above account managers who have not.
- Your leadership has visible consequences. Delivery cadence, quality, and reliability are measured monthly and reviewed by the customer. The organization you build performs in public.
- Direct customer access. You work with federal decision-makers yourself. Your judgment reaches the people who act on it, without three layers of translation in between.
- You build the machine. You are establishing how engineering delivery works on this program, not maintaining someone else's operating model.
- AI-native is practice, not positioning. AI is part of how PhoenixTeam delivers, and we fund ongoing AI education and development for the entire team. In this role you will scale that investment across an organization, not fight for permission to use it.
- Fully remote,S.-based, permanently.
- Competitive salary and 100% employer-paid medical insurance.
- Mission you can explain at dinner. The software your teams ship supports a home loan benefit for the people who served this country.
Position Requirements
- Full-time W-2 employment with PhoenixTeam.
- Must be based in the United States.
- Fully remote.
- Work supports a federal civilian agency.
- Must be able to obtain and maintain the required federal Public Trust clearance. A Secret clearance is not required.
PhoenixTeam is a woman-owned small business focused on federal and commercial housing finance technology.
Similar Jobs
What you need to know about the Boston Tech Scene
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories


