Job Title: AI Engineer
Location: NYC, Onsite
Compensation: $170,000 – $180,000 + equity
Role: AI Engineer
A stealth-stage startup backed by experienced operators is hiring its first core technical team member to build the infrastructure powering LLM-native agents. These agents are being designed to replace manual research workflows for professionals in high-stakes industries – enabling faster, smarter decisions through structured automation.
This is a greenfield opportunity to architect the full backend stack for an AI-first product used by design partners at top-tier firms. You’ll work side by side with the founders to define the tech, ship fast, and iterate directly with users.
Why This Role Matters
AI agents are maturing beyond chat – this role is focused on building real systems for real work. You won’t just be calling OpenAI APIs; you’ll be orchestrating multi-step reasoning chains, integrating retrieval systems, and designing LLM infrastructure with performance, observability, and execution in mind.
If you’ve shipped real AI infra and are looking for end-to-end ownership, direct product impact, and early equity, this is the moment.
What You’ll Do
- Architect and own the backend and infra stack from MVP to scale
- Build and maintain agent orchestration pipelines using LangGraph-style frameworks
- Develop retrieval and indexing systems (e.g. vector DBs, RAG workflows)
- Collaborate with founders and early design partners to iterate quickly
- Build robust interfaces, deployment pipelines, and execution logic across the agent stack
- Operate in a fast, unstructured environment with autonomy and trust
Tech Stack
- Languages/Frameworks: Python, TypeScript
- Infra: Docker, cloud infra (AWS/GCP), CI/CD pipelines
- AI Tools: LangGraph, LangChain, CrewAI, vector DBs (Weaviate, Pinecone), RAG pipelines
- Architecture: Microservices, agent orchestration, ingestion & execution flows
Ideal Candidate
- Strong backend or platform engineer with experience owning infra in a 0→1 setting
- Hands-on with AI orchestration tools, LLM APIs, retrieval pipelines, or multi-agent systems
- Comfortable with cloud deployment, observability, and fast iteration loops
- Startup-ready mindset: low ego, high autonomy, shipping > perfection
- Bonus: past experience with LangGraph, RAG, or building structured LLM workflows
About Us
People In AI partners with fast-moving startups and applied AI companies to hire with clarity and technical precision. We connect mission-aligned engineers and scientists with founders building real AI products — not just prototypes.