Full-Stack Software Engineer (Agents & Rapid Prototyping)Location: Remote (US-friendly hours)
Type: Full-time (founding/early engineer)
Team: Small, passionate, ego-free builders
Why this roleWe're hunting for
product-market fit. That means we ship POCs fast, test hypotheses daily, and aren't afraid to throw work away if the data says so. If you
code for fun, ask "
why" before "
how," and love turning messy problems into scrappy automation that actually saves people time-this is your playground.
What you'll do- Prototype at lightning speed: Build and ship POCs, internal tools, and production features in days-not weeks.
- Work with LLMs & SLMs: Integrate, evaluate, and fine-tune models; design agentic workflows that reduce manual work.
- Automate the boring stuff: Sniff out bottlenecks, redundancies, and paper cuts; replace them with lightweight automations.
- Balance build vs. buy: Pragmatically choose off-the-shelf services vs. custom code; optimize for speed, cost, and learning.
- Own the stack end-to-end: APIs, data models, frontends, deployments, instrumentation, and on-call for what you build.
- Collaborate without ego: Pair with design, product, and GTM to clarify the "why," define thin slices, and ship continuously.
- Ruthlessly iterate: Be comfortable restarting weekly if needed; measure outcomes, not lines of code.
Outcomes (how we'll measure success)- 2-3 prod-quality launches/month from idea → shipped.
- Clear learning loops: each release produces measurable signal (conversion, retention, time-saved).
- Automation ROI: hours saved/team/week; decreased cycle time; reduced ops tickets.
- Agent impact: at least one agent in steady use by internal or pilot users within first 60 days.
You might be a fit if you- Have 4+ years building full-stack products (or equivalent portfolio/hacker track record).
- Are fluent in a modern web stack (e.g., TypeScript/Node, Python, React/Next; Postgres/Redis; REST/GraphQL).
- Have shipped LLM/SLM features (tool use, RAG, function calling, evals, latency/cost tuning).
- Can design simple, resilient backends; write clean, testable code; and deploy via CI/CD to a major cloud.
- Love debugging with data: logs, traces, metrics; you instrument before you guess.
- Communicate crisply, ask sharp questions, and default to action.
- Thrive in ambiguity; you don't need a JIRA novella to start building.
Nice to have- Vector DBs, embeddings, prompt/version management, offline evals.
- Agent frameworks (e.g., OpenAI tools, LangGraph, custom planners/executors).
- Queueing/event systems (e.g., Kafka, SQS), WebSockets, streaming.
- Security and privacy basics (authn/z, secrets, PII handling).
- Experience with low-cost scrappy stacks (Cloudflare, Fly.io, Supabase, Firebase).
Our stack (evolving)- FE: React/Next.js, Tailwind, tRPC/GraphQL
- BE: Node/TypeScript and/or Python FastAPI
- Data: Postgres, Redis/Upstash, optional vector store
- Infra: Vercel/Fly.io/Cloudflare + Docker; CI/CD (GitHub Actions)
- AI: OpenAI, Anthropic, local SLMs when useful; evaluation harness + prompt/version control
How we work- Learn > Perfect: Ship thin slices, get signal, iterate.
- Write it down: Short RFCs → prototype → user feedback within days.
- Builder culture: No rockstars, no heroes-just ownership and curiosity.
- Time-zone friendly: Async first; quick huddles when needed.
Interview flow- Intro chat (30 min): goals, mindset, what great looks like.
- Builder exercise (home or live, 2-4 hrs): ship a tiny agent or automation; explain trade-offs.
- Technical deep dive (60 min): architecture, data modeling, reliability, AI evals/cost.
- Team fit (30 min): collaboration, feedback loops, "why before what."
CompensationCompetitive salary + meaningful equity. We optimize for
ownership and
impact.