Founding AI & Product Engineer

Overview

At Lupa, we're hiring a Founding AI & Product Engineer for an AI-native real estate investment and private-credit platform. This is a maker's seat for an engineer who wants to be in the code every day — not a figurehead, not a delegator, and not a management-only CTO role.

The systems are already live and the product roadmap is already written. What's needed is the person who will own the full stack, ship against that roadmap, and eventually build a nearshore engineering team around it. You'll inherit working, founder-built systems — an AI research and market-intelligence stack, plus a greenfield mortgage-platform operating system — take over their architecture, and turn a two-to-three-year plan into shipped, durable software.

The reason to want this seat is the building. You'll have unusual proximity to the decisions the software is meant to improve, working directly with the people who source deals, underwrite markets, approve credit, and manage capital. There is no handoff to an abstract product org: you help decide what matters, build it, and watch it operate in the real world.

What You'll Do

• Own the full stack end to end — application, database, cloud, security, observability, data contracts, model integration, and release discipline.

• Take over and evolve an existing AI research and market-intelligence system: ingestion pipelines, production agents, source-aware synthesis, data integrity, and the user-facing dashboards they feed.

• Co-build and then internally own a mortgage-platform operating system — the management, intelligence, and portfolio layer around specialist loan-manufacturing and servicing systems.

• Build data-intensive workflows: ingestion, orchestration, structured extraction, validation, reconciliation, lineage, async jobs, and third-party API integrations.

• Design and ship geospatial and collateral-intelligence features (parcel data, mapping, multi-source property dossiers) and governed, auditable decision records.

• Establish the engineering operating system: CI/CD, test coverage, migrations, infrastructure as code, security controls, model/data evaluation, incident response, and clear documentation.

• Recruit, direct, and set the quality bar for a nearshore engineering team as the roadmap grows — while continuing to write production code yourself.

• Partner directly with leadership and domain experts to translate the decisions they're trying to make into clear system behavior.

Who You Are

Must-haves

• An engineer genuinely obsessed with building — you'd rather ship a system than run a meeting about one.

• Roughly 4–8 years building production full-stack systems inside a demanding engineering organization, with architecture you personally designed, shipped, and operated.

• Strong across system architecture, service boundaries, data modeling, database migrations, APIs, cloud infrastructure, security, and observability.

• Fluent in Python, TypeScript/JavaScript, SQL, and Postgres, with production experience in modern web patterns — React and FastAPI especially relevant (equivalent depth in adjacent frameworks transfers).

• Experienced with data-intensive workflows: ingestion, orchestration, structured extraction, validation, lineage, and third-party APIs.

• AI-native in the practical sense: aggressive use of frontier coding tools, plus real understanding of agent/tool systems, structured outputs, evaluation harnesses, model failure modes, and human-in-the-loop controls. Prompt fluency alone is not enough.

• Product-minded and commercially curious; self-directed and comfortable with ambiguity in a fast-moving, founder-led environment.

• Strong professional English — you'll touch both internal and eventually external-facing systems and work closely with US leadership.

Nice-to-haves

• PostGIS, geospatial data, parcel systems, mapping, or 3D visualization.

• Fintech, private credit, mortgage, real estate, or other regulated, data-intensive financial products.

• Multi-tenant enterprise apps, role-based access, audit trails, and sensitive-data controls.

• Dagster or similar orchestration; data contracts, governed marts, event sourcing, model/data provenance.

• Experience inheriting founder-built systems, integrating external dev teams, or bringing prototypes into durable production.

Industry pedigree is not the deciding factor — current technical depth, judgment, and learning velocity matter more than prior asset-management experience.

What's In It For You

• Compensation: USD $100,000–$120,000 base for a senior, hands-on hire.

• Engagement model: Long-term, direct hire — this is a foundational seat, not a short-term contract, with the mandate to build a team over time. .

• Location & remote: Remote / flexible, with LatAm-based candidates welcome. Periodic in-person New York working sessions expected (roughly twice a year, about a week each).

• Growth: Report directly to the Co-Founder & General Partner as the first dedicated engineering hire, with a clear path to standing up and leading a nearshore engineering team — while staying hands-on in the code.

• Impact: Direct proximity to the business decisions your software drives, real ownership from week one, and the chance to define the technical backbone of an AI-native platform.

Application

If you're a builder who wants to own consequential systems from day one — and grow a team around you without ever putting down the keyboard — we'd love to hear from you. Apply through Lupa with your CV and links to systems you've personally built and shipped to production. The strongest thing you can show us is what you've built and operated in the real world.