🚀 Founding AI Engineer
Location: San Francisco, CA (onsite only)
Salary: $120-$250k + meaningful equity
About us:
We are reimagining how people meet, starting with dating. We’re building the first fully agentic social platform, where AI does the heavy lifting: understanding user preferences, finding compatible matches, and even setting up real-life dates.
We are live across multiple college campuses, we've enabled tens of thousands of real dates, and raised funding from Google and top-tier VCs, alongside engineers and researchers from MIT, Stanford, Berkeley, and DeepMind.
Dating is just the beginning. We’re here to disrupt the entire social scene.
What You’ll Do
- Ship agentic matchmaking systems from research to production, owning retrieval, reasoning, tool use, and safety end-to-end
- Build human-like AI chat agents, optimizing for latency, consistency, and perceived realism
- Design and maintain context engineering pipelines (RAG, memory, summarization, grounding, compression)
- Create prompt and model evaluation harnesses (offline + online) with A/B testing and rapid iteration
- Stand up observability for agents (traces, cost, failures, hallucinations, guardrails) and product-facing dashboards
- Collaborate daily with cofounders and product to translate user problems into shipped agent behaviors
- Write clean, maintainable code and build internal tools and SDKs used by engineers and AIs
What We’re Looking For
- 2–4+ years of relevant experience or an exceptional portfolio of LLM/agent projects (GitHub, demos, write-ups)
- Strong programming fundamentals (data structures, algorithms, testing, profiling)
- Proficiency in TypeScript (product code, services) and Python (model ops, evals, data)
- Experience working with multiple LLM providers, tool/function calling, and model fallbacks
- Hands-on experience with RAG (indexing, embeddings, reranking) and practical prompt engineering
- Ability to define metrics and KPIs (accuracy, latency, cost, safety), run A/B tests, and incorporate human feedback
- Comfortable with MongoDB in production; experience with vector databases is a plus
Bonus: Agent frameworks (LangGraph, CrewAI), LLM eval/observability tools (Langfuse, Promptfoo, Ragas, TruLens), MCP, retrieval systems, or safety/guardrails work.
If this sounds like you, apply below, we’d love to hear from you.
