Founding AI Engineer

Edge Tech•San Francisco, CA

1d•$175,000 - $250,000•Onsite

About The Position

We’re working with a stealth AI startup building agentic AI systems that automate complex chip verification and debugging workflows . Today, debugging a single issue in chip verification can take days and multiple engineers digging through tools, logs, and simulation environments . This company is building AI agents that reduce those workflows to minutes. The platform captures how the best silicon engineers solve problems and turns that knowledge into AI playbooks that scale across entire engineering teams . Customers already include fast-moving semiconductor startups and large publicly traded chip companies. They’re now hiring a Founding AI Engineer to help build the core intelligence layer powering these agents. This is a true 0 → 1 role where you’ll design systems, ship production models, and directly shape the future of AI in hardware engineering.

Requirements

Production AI Builders 3+ years building and shipping real AI systems , ideally agent-based or complex ML systems in production.
Strong ML Engineering Hands-on experience with Python, PyTorch, and modern ML workflows .
Post-Training / RL Experience Experience with RLHF, DPO, reward modeling, or similar post-training techniques is a strong plus.
Startup or Founder DNA Former founders, founding engineers, or builders who have shipped technically complex products.
Technical Depth Strong background in computer science, computer engineering, or electrical engineering (top university backgrounds preferred).

Nice To Haves

Silicon verification workflows
EDA tooling (Synopsys, Cadence, Questa)
Publications in top conferences (NeurIPS, ICLR, DAC)

Responsibilities

Build the Intelligence Layer Design and implement post-training pipelines that shape how AI agents reason about chip verification workflows.
Reinforcement Learning Systems Develop reward models, RLHF / RLAIF pipelines, and evaluation harnesses that improve agent decision-making over time.
Agent Tooling & Execution Systems Build the infrastructure that allows models to interact with real engineering environments and EDA tools .
Production AI Systems Ship agentic AI systems used directly by semiconductor engineers solving real verification challenges.
Customer-Driven Intelligence Work closely with silicon engineers and customers to encode domain knowledge into training data, reward signals, and evaluation frameworks.
Frontier AI Work Stay close to advances in LLM reasoning, agentic architectures, and reinforcement learning , bringing new ideas directly into production.