About GoodLeap:
GoodLeap is a technology company delivering best-in-class financing and software products for sustainable solutions, from solar panels and batteries to energy-efficient HVAC, heat pumps, roofing, windows, and more. Over 1 million homeowners have benefited from our simple, fast, and frictionless technology that makes the adoption of these products more affordable, accessible, and easier to understand. Thousands of professionals deploying home efficiency and solar solutions rely on GoodLeap’s proprietary, AI-powered applications and developer tools to drive more transparent customer communication, deeper business intelligence, and streamlined payment and operations. Our platform has led to more than $30 billion in financing for sustainable solutions since 2018.
GoodLeap is also proud to support our award-winning nonprofit, GivePower, which is building and deploying life-saving water and clean electricity systems, changing the lives of more than 1.6 million people across Africa, Asia, and South America.
The Strategic Initiatives team builds internal software and financial models that run parts of GoodLeap's lending programs.
The Manager, Strategic Initiatives has real finance, analytical, or operations depth and is curious enough about AI to learn it on their own and teach others. The Manager owns an area of the team's work end to end, from the first conversation with a business user through a shipped, working result, and stays accountable for it after it ships. This person also manages one or more Senior Associates: reviewing their approach, coaching their use of AI coding agents, and making sure their work is sound before it reaches a user. This is a player-coach role. The Manager builds directly, at least early on, rather than only reviewing others' work.
Essential Job Duties and Responsibilities:
Ownership:
Own an assigned area of the Strategic Initiatives portfolio, including the relationship with its business users and the reliability of anything shipped into their hands.
Set priorities for that area in partnership with the Director and defend the reasoning behind them.
Make day-to-day technical and product decisions independently; escalate architecture or infrastructure calls that affect the wider portfolio rather than deciding those alone.
Building With AI Agents:
Use AI coding agents personally to build financial models, internal tools, and product features, staying hands-on rather than moving straight into pure oversight.
Set the standard for how the team uses AI agents responsibly: what gets reviewed, what gets tested, and what never gets touched without a second set of eyes (production data, permissions, anything user-facing).
Recognize when AI-generated work is subtly wrong, not just obviously broken.
Managing and Developing Associates:
Manage one or more Senior Associates: their workload, their growth, and the
quality of what they ship.
Teach associates how to work with AI coding agents effectively, using real,
current work rather than generic training.
Review associates' output for judgment, not just correctness: did they solve
the actual problem, or just the stated one.
Stakeholder Management:
Work directly with business and executive stakeholders, including COO-level
leadership, on the status and results of your area.
Translate ambiguous, sometimes shifting business asks into a clear plan the
team can execute against.
Communicate tradeoffs and risk plainly, including when the honest answer is
'not yet' or 'not like that.'
Required Skills, Knowledge and Abilities:
Bachelor's degree in Finance, Business, Economics, or a related quantitative field; MBA a plus but not required.
5+ years of experience in finance, strategy, operations, or a related analytical role, including at least a year applying AI tools to real work product.
Some experience managing, mentoring, or training junior colleagues, formally or informally.
Curiosity: a demonstrated habit of teaching yourself new tools before anyone asks you to, including AI tools specifically.
Perseverance: a track record of carrying an ambiguous, difficult problem to a finished result, not handing it off when it gets hard.
Critical thinking: the ability to take a messy business problem apart, find the real question, and defend your answer to a skeptic.
No prior software engineering background required. What matters is technical fluency good enough to direct AI coding agents, evaluate their output, and teach someone else to do the same.
Comfort being personally accountable for the production outcome of something built primarily with AI assistance.
Experience with internal software, financial services, lending, or AI systems is a plus but not required.
