Senior AI Engineer (Studio)
Summary
Senior AI Engineer at AIVC's venture studio, building end-to-end agentic AI systems (agents, retrieval, orchestration) for new ventures from zero to product-market fit. Hybrid role in New York (Flatiron) or Chicago; Python/LLM stack; $190k-$250k plus equity.
Senior AI Engineer (Studio)
Company: Confidential — venture-backed technology company
Location: New York, NY (Flatiron, 21st & Broadway) or Chicago, IL (hybrid, 3 days in office)
Compensation: $190,000 - $250,000 + competitive equity
Employment Type: Full-time
Visa Sponsorship: Visa transfers (OPT, H-1B transfer)
About the Company
The client's Studio turns validated venture concepts into shipped AI products with real users, building new companies from zero to product-market fit, with offices in New York and Chicago.
The Role
The client is hiring a Senior AI Engineer (3-7 years) to join its Studio as a core builder. You are a quant-aspiring or big-tech engineer with an entrepreneurial streak who has shipped end-to-end AI systems to production, builds things nobody asked for, and wants real ownership in the companies you help create.
What You Will Do
- Build end-to-end agentic AI systems (agents, retrieval, orchestration, tool integrations) for Studio ventures from 0 to 1 through product-market fit.
- Take a venture's first product from scope to ship, cutting to the smallest thing that proves value and then hardening it for production.
- Extract reusable primitives so each new venture starts further ahead.
- Work with product strategists and design partners to shape what gets built.
- Operate across very different venture contexts and thrive in ambiguity.
What You Bring
- 2-5+ years at a top quant firm (Citadel, Two Sigma, DE Shaw, Jane Street) or an elite tech company (Google, Stripe, Ramp, Databricks, Modal), with clear individual output
- End-to-end AI systems shipped to production with real users
- Demonstrated entrepreneurial instinct: a side project, startup, internal 0-to-1 or innovation inside a large org
- A STEM degree (CS, Math, Physics or Engineering) from a top university
- Commercial EQ with non-technical stakeholders, customers and design partners
Tech Stack
Python, LLMs, agentic AI frameworks, RAG and retrieval systems, ML model serving, evaluation and regression suites, CI/CD, observability
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