Applied AI Engineer, Startups (Physical AI)

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 as they grow from early product to scale.

You will lead deep technical engagements, partnering directly with startup software and hardware engineering teams to help them build products on Claude and run their own engineering processes with it. You will bridge the gap between what Claude can do and what it takes to build physical systems, advising on implementation and agent design.

Responsibilities

• Serve as a deep technical advisor to high-potential startups building in the physical world, helping push the boundaries of AI in engineering, manufacturing, operations, and more.
• Work hands-on with startup software and hardware teams through pair programming and architecture reviews to accelerate development.
• Develop prototypes and technical documentation, including evaluation suites, benchmarks grounded in real engineering tasks, AI engineering techniques, and architecture diagrams.
• Create reference implementations and sample code for common integration points, such as 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 (e.g., reading drawings, 3D geometry, board layout and routing, GD&T, latency, on-premise constraints, physical safety) 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.

Qualifications

• Deep engineering experience in a physical discipline such as mechanical, electrical, aerospace, robotics, semiconductor, manufacturing, or civil engineering, gained by designing, building, or operating real hardware.
• 4+ years of technical experience as a software engineer, ML or research engineer, robotics or controls engineer, hardware or systems engineer, or technical founder.
• Either production experience building LLM-powered applications (including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale) or a track record of successfully applying AI to real engineering work in design, simulation, test, or production.
• Experience with startups or high-growth companies and working with founders and small teams.
• Strong technical communication skills to translate complex AI concepts into architectural decisions for both software and hardware audiences.
• Bachelor’s degree or an equivalent combination of education, training, and/or experience in a relevant field.