Founding Technical Lead
Founding Technical Lead – Equity Forge
About Equity Forge
Equity Forge is building infrastructure that transforms how people build skills and wealth—creating pathways from verified volunteering → paid marketplace work → startup equity participation, all on one platform.
We're a spinoff of DemocracyLab, which has facilitated over 10,000 skilled volunteer placements since 2018. Our core innovation is professional identity built on verified evidence—activity tracking, peer attestation, documented outcomes. When credentials are trustworthy, they become worth investing in, and that investment compounds over time.
The Role
We're looking for a Founding Technical Lead to own our technical direction. You'll evaluate our existing codebase, make architectural decisions, and build the systems that differentiate our platform—while leading the engineering team as it grows.
You'll be the technical leader from day one. As we hire additional engineers, you'll shape when and how the team grows, and you'll direct their work. You'll own the codebase and the decisions that shape it.
Equity Forge operates on a dynamic equity model—contributors earn ownership proportional to their contribution. This role is equity-only, which means you'll have significant ownership stake in what we're building together.
The Technical Landscape
We have a production Django/React application (CivicTechExchange) that powers DemocracyLab's volunteer matching platform. The codebase was built primarily by our Lead Developer Emeritus over several years, with contributions from many volunteers. It works. Whether it's the right foundation for what we're building next is an open question—and one you'll help answer.
The Work
Improving the existing platform. There's substantial feature work to bring the application up to modern standards: a real matching algorithm (currently users rely on filters and search), streamlined project editing, account deletion, and numerous other improvements. These don't require exotic technology—they require solid engineering and clear priorities.
Building three new systems:
Proof – Verified professional identity through work tracking, peer attestation, and documented outcomes
Accord – Communication quality during hiring—required responses, civility metrics, real-time engagement tracking
Mosaic – AI-powered representation that transforms verified data into evidence-backed professional narratives
These systems have real technical requirements: AI integration (RAG pipelines, embeddings, LLM-powered generation), real-time coordination (WebSockets, presence), and high concurrency. Python's AI/ML ecosystem is why we're hiring for this stack.
The Architectural Decision
Your first major responsibility is evaluating the codebase and recommending the technical path forward. This decision shapes everything that follows—both how we improve existing functionality and how we build Proof, Accord, and Mosaic.
Options include:
Refactor Django in place — Clean up the existing codebase, add Django Channels for real-time features, build everything within the current architecture
Strangler fig migration — Build new functionality in FastAPI from the start; migrate legacy features incrementally until Django is fully replaced
Selective modernization — Build AI-heavy systems in FastAPI, but keep stable legacy features in Django permanently; only migrate what needs significant work anyway
Greenfield replacement — Start fresh, migrate data, deprecate legacy entirely
We're not prescribing the answer. We need your judgment. Our priorities, in order:
Right technologies for what we're building long-term. Proof, Accord, and Mosaic are the product—optimize for them.
A codebase that's logical and welcoming to new engineers. We're building a team; the architecture should be learnable.
Architecture that adapts to the changing AI-coding landscape. AI tools are accelerating development; our codebase should work well with them.
Minimize unnecessary work. Don't rebuild what doesn't need rebuilding.
What You'll Do
Evaluate the existing Django/React codebase and recommend the technical path forward
Make architectural decisions and communicate them clearly
Ship improvements to the existing platform—features users need now
Build AI-integrated systems (Proof, Accord, Mosaic) using Python's ML ecosystem
Establish engineering practices and patterns that scale with the team
Help hire and direct additional engineers as we grow
Use AI coding tools (Claude Code, Cursor, GitHub Copilot) to accelerate development
What We're Looking For
Required
Strong Python experience (Django or FastAPI in production)
Ability to evaluate inherited codebases and make pragmatic decisions
Experience with AI/ML integration (LangChain, embeddings, LLMs, or similar)
Good judgment about tradeoffs in resource-constrained environments
Comfort leading other engineers' work
Interest in the mission: accelerating innovation and creating shared prosperity by democratizing economic opportunity
Clear written and verbal communication. We're fully remote and coordinate over Slack and Google Meet.
Valuable
React frontend experience
FastAPI (potential migration target)
RAG pipeline implementation
Marketplace or platform development
AWS infrastructure (RDS, ECS)
Experience hiring or building engineering teams
Compensation & Commitment
This is an equity-only role using the Slicing Pie dynamic equity model. Your ownership stake grows proportionally with your contribution. There is no cash compensation currently. Time commitment is flexible—we care about consistent progress and reliable collaboration, not rigid schedules.
This is a fully remote position.
We welcome applicants regardless of location. Our operating agreement specifies Oregon, USA jurisdiction; we'll work through additional considerations for international contributors during the process.
This role makes sense if you:
Want meaningful ownership in something you're building from the ground up
Are excited about AI/ML integration in production systems
Care about the mission—democratizing economic opportunity and creating shared prosperity
Have financial runway to work without immediate income
Team & Context
You'll join a small team with significant ownership. Our Lead Developer Emeritus can provide context on the existing codebase, and you'll have access to experienced technical advisors.
The broader team includes experience from Amazon, Microsoft, Google, Indeed, LinkedIn, and more—people who chose equity participation because they believe this should exist.
To Apply
Send a note to [email protected] explaining:
Why this opportunity interests you
Your Python experience, particularly with AI/ML integration
How you approach architectural decisions when inheriting a codebase
Your current situation and capacity to contribute
Any questions about the role, the systems we're building, or the equity model