Applied AI Engineer, Startups (Physical AI)
Anthropic- Compensation
- $280k–$320k Published range · Top quartile for Engineering (811 listings)
- Location
- Hybrid - San Francisco, CA, 25% in office Remote eligibility
- Employment
- Full-time Mid-level
About the job
About the role
As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to top AI-native startups building in the physical world, across robotics, semiconductors, aerospace, manufacturing, and civil infrastructure. You'll lead deep technical engagements, partnering directly with startup software and hardware engineering teams to help them build their products on Claude and run their own engineering with it, advising on implementation and agent design.
Responsibilities
- Serve as a deep technical advisor to high-potential startups building in the physical world.
- Work hands-on with startup software and hardware teams through pair programming and architecture reviews.
- Develop prototypes and technical documentation, including evaluation suites, benchmarks, and architecture diagrams.
- Create reference implementations and sample code, for example integrating Claude with CAD, simulation, design tools, or industrial automation.
- Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements.
- Identify patterns across engagements and build repeatable evaluations and solutions.
- Create technical content for startup audiences including documentation, tutorials, and sample code.
- Foster community engagement through hackathons, webinars, technical office hours, and startup-focused events.
- Travel to customer sites for workshops, implementation guidance, and relationship building.
You may be a good fit if you have
- Deep engineering experience in a physical discipline such as mechanical, electrical, aerospace, robotics, semiconductor, manufacturing, or civil engineering.
- 4+ years of technical experience as a software engineer, ML or research engineer, robotics or controls engineer, hardware or systems engineer, or technical founder, with either production experience building LLM-powered applications or a track record of successfully applying AI to real engineering work.
- Experience with startups or high-growth companies.
- Strong technical communication skills.
- A collaborative approach and the range of a generalist.
Logistics
Minimum education: Bachelor’s degree or equivalent. Required field of study: A field relevant to the role. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. Visa sponsorship: We do sponsor visas.
Skills & tags
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