Founding AI Engineer

The future will have more chips, in more varieties, for more applications than ever before. The current way of designing, testing, and manufacturing them can't keep up. Outdated chip development processes are the present rate limiter on humanity's future.

Bronco's mission is to keep Moore's law going by building AI agents that automate large swaths of repetitive chip verification and design.

We're backed by tier-1 Silicon Valley investors and deployed with some of the largest chip companies in the world, supporting production SoC designs at leading-edge process nodes.

As a Founding AI Engineer, you will own the core intelligence of Bronco's agents. That means designing the training pipelines, reward models, and evaluation harnesses that will make sure our agents actually succeed not just in benchmarks but on real production tapes.

The ideal candidate has built and shipped agentic AI systems as a founder, as a founding engineer, or as part of an industry research lab. You are high agency, know how to attack a problem, and can build the infrastructure to systematically make your systems better.

• →Design and implement post-training pipelines for domain-specific model behavior across DV tasks — testbench generation, bug triage, coverage closure
• →Develop reinforcement learning setups, including reward modeling and RLHF/RLAIF pipelines, to improve agent decision-making on long-horizon verification tasks
• →Build tool interfaces, scaffolding, and execution harnesses that allow models to interact reliably with EDA environments and RTL artifacts
• →Iterate with silicon domain experts and customers to encode verification knowledge into training data, reward signals, and evals that measure real agent capability — not proxy metrics
• →Stay current with frontier research in LLM reasoning, RL for agents, and tool use — and bring what's relevant into production

• You have shipped agentic AI systems that work in the real world
• Experience at an industry research lab, as a past founder, or as a founding engineer at an AI startup
• Deep hands-on experience with post-training: RLHF, DPO, or equivalent
• Experience designing evaluation frameworks for LLM or agentic systems
• Strong proficiency in Python and PyTorch

• Background in Electrical or Computer Engineering
• Familiarity with chip design and verification workflows
• Experience with EDA tools (Synopsys, Cadence, Questa, etc.)
• Publications at NeurIPS, ICLR, ICML, DAC, ICCAD, or DVCon