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Salary
≈ $166k – $370k per year (Estimated)
Location
In office (San Francisco)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Aug 6, 2024. Bronco AI scores B on the Alion truth index.

Overview
Company
Impact
Profile match
AI for chip design and verification. Bronco debugs simulations, brings up testbenches, generates RTL, and closes coverage to win the race to tape-out.
Backed by Y Combinator

About Us

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 Outdated chip development processes are the present rate limiter on humanity's future.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.

About the Role

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.

What You'll Do

  • 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

We'd Like to See

  • 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

We'd Prefer If You Had

  • 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

What We Offer

  • Competitive salary and equity package
  • Comprehensive benefits including health, vision, dental, housing stipend, and 401(k) with match
  • High-ownership, high-velocity environment with rapid learning opportunities
  • A technical problem that is the present rate limiter on the future
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