Full Stack Engineer

What You'll Work On

Full ownership, front to back

Build complete features end-to-end: APIs, business logic, data models, and the interfaces that users actually touch.

Move fluidly between backend services (Java, Python) and modern frontend work without needing a handoff to unblock yourself.

Ship features you can point to — visible, real, in production.


AI-native development as a core skill

Use AI coding assistants and LLM-powered workflows as a genuine part of how you build — across the stack, across the lifecycle.

Lean on AI to accelerate the parts of the stack that are less familiar: generate a solid starting point, validate your approach, and iterate from there.

Develop one of the most marketable engineering skillsets available right now — with the team and the mandate to go deep on it.

Hard problems in a meaningful domain

Work at the intersection of identity, trust, and compliance — problems with real stakes and technical depth.

Design and build systems where correctness matters: data integrity, verification workflows, and integrations with external providers.

Contribute to architecture discussions with a practical point of view, and grow your instincts by working alongside engineers who've seen these patterns before.


Continuous growth

Pair with senior engineers who are invested in your development, not just your output.

Participate actively in code reviews and design conversations — your perspective matters here.

Build fluency across the stack in a production environment, with real feedback loops.

What We're Looking For

Must-Have

3+ years of professional experience building and shipping software across both frontend and backend.

Solid backend fundamentals in Java and/or Python — you understand what's happening under the hood.

Hands-on frontend experience with a modern framework (React preferred) — you can build a functional, clean UI without it being your primary identity.

Comfort with REST APIs, data modeling, and connecting the layers of a system end-to-end.

Curiosity about AI development tools and at least some hands-on experience — you're building the habit even if you're not fully there yet.

Strong written and verbal communication skills and comfort collaborating in a hybrid environment.

Nice to Have

Experience with cloud infrastructure (AWS, GCP, or Azure), CI/CD pipelines, or containerized deployments.

Exposure to LLM integrations in production environments.

Background in identity, privacy, or compliance-adjacent products.

Experience in fast-moving startup or scale-up environments.

What You'll Get Out of This

• Full stack fluency, for real. Most roles keep you siloed. This one will stretch you across the entire product surface — by design.
• Mentorship from people worth learning from. The team is small, experienced, and the kind that shares what they know.
• AI skills that actually matter. You'll build genuine depth in AI-assisted development inside a production environment, on a team that takes it seriously.
• Ownership without bureaucracy. Small team, real decisions, no ticket factory.
• Work worth caring about. Identity verification sits at the center of trust online — the problems have weight.
• Competitive compensation, benefits, and a hybrid work setup based out of Atlanta, GA.