Job Description
Job Description
Founding AI Engineer
Location : New York City (Onsite, full-time)
Compensation : Base salary $200,000–$250,000 plus 0.5%–1.5% equity
About the Company
A venture-backed, revenue-generating healthtech startup is building an AI-native operating system for modern medicine . The mission : make personalized, data-driven private care radically more accessible and affordable across all 50 states. Small, high-output team of engineers, clinicians, and repeat founders; actively deploying AI agents in real clinical settings with measurable ROI.
The Opportunity
As the Founding AI Engineer , you will architect and build the horizontal enablement layer that powers the company’s AI platform. This role blends systems architecture, applied AI, information retrieval, and data engineering —with a fast path to technical leadership and team-building .
What You’ll Do
- Architect AI data pipelines : ingestion, chunking, metadata, embeddings, and retrieval at scale.
- Build Applied AI / Agentic systems : low-latency agents, deep-research / ambient agents, and long-running event-based agents for clinical workflows.
- Develop retrieval & search : semantic + hybrid (lexical, vector, faceted, LLM-enhanced) search over unstructured medical data, relational DBs, graphs, and object stores.
- Structure messy data : extract / transform from PDFs, JSON, EHR exports into robust schemas for downstream AI.
- Own quality & performance : define metrics (retrieval accuracy, latency, data quality), optimize throughput and cost.
- Collaborate & lead : partner with backend / frontend teams; drive reviews, docs, and architectural guidance; mentor future ML / AI hires.
Tech Stack You’ll Touch
Frontend : React, Next.js (App Router), Tailwind, TanStackBackend : Python (FastAPI), TypeScript (Nest.js)LLM & Retrieval : OpenAI, Anthropic, Gemini; AI Vercel SDK; OpenAI Agents / tool-calling; instructor; LiteLLM; SQL / pgvector; GCSInfra : GCP (Vertex AI, Pub / Sub), Terraform, modern CI / CD / observabilityWhat We’re Looking For
5+ years in AI / ML engineering or data infrastructure.Deep knowledge of embeddings, RAG / hybrid retrieval, vector databases, context / memory management .Hands-on experience building search / retrieval pipelines (ingestion → processing → indexing).Strong software engineering fundamentals (modular architecture, testing, CI / CD, observability).Up to date on the Applied AI ecosystem (neural RAG, rerankers, multi-agent orchestration, tool calling, structured streaming outputs).Passion for solving high-impact, real-world data problems (healthcare / life sciences a plus).Nice to Have
Multi-tenant architectures; RBAC and data governance.Prior biotech / healthtech / clinical informatics experience.IR evaluation expertise ( precision@k, recall@k, MRR ).Engagement with the “AI Engineer” community.Why This Role
Mission-driven impact : Agents already live in clinics; your work reduces provider burnout and improves patient outcomes.Founding seat : Define architecture, standards, and culture from day one.Category creation : Help build the stack for the next era of personalized medicine.