Join the team bringing autonomy to the built world

At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs.

In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic

In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.

This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.

About the Role & Team

Bedrock's Product team decides what our autonomous machines should learn to do next. We also make sure the people who work alongside them get real value from them: operators, site managers and the construction companies we partner with. Our problems rarely arrive as specs. Which task or machine type is worth taking on next? How do you turn "digs like an expert" into a number you can measure? What does a partner need to see before trusting a 40-ton machine on their site?

As our Product intern, you'll get a problem like that, not a task list, and own it for the summer. You'll frame it, work out the answer, build what's needed, and bring the team a recommendation they can act on. You'll work the way our team does: with AI tools in hand, going from question to working prototype in days, not weeks.

What You'll Do

• Own an open product problem end to end: frame it, find the data and the people who know, decide what to build, and ship it before the summer ends
• Turn fleet data from real jobsites into decisions: how well our machines perform, where they struggle, and what that means for what we build next
• Prototype with AI coding tools and agents: internal tools, data pipelines, automated workflows, and working demos that make an idea concrete instead of slides about it
• Spend time at our field sites with operators and site teams, and turn what you see into requirements engineers can build against