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San Francisco, California, United States
Hybrid
Available
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
As an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the 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. Some of these companies build the hardware itself and want Claude woven into how they design, test, and operate it, and others build the software that engineers everywhere use to design, simulate, test, and scale, and this role works with both. 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 as they build what is newly possible with AI in the physical world. You will bridge the gap between what Claude can do and what it takes to build real things, working alongside some of the strongest teams in the field on problems that matter and helping mechanical, electrical, and process engineers get the kind of step change that software engineering has had from agentic coding with tools like Claude Code.
Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your engineering domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable physical AI startups to succeed with Claude.
Serve as a deep technical advisor to high-potential startups building in the physical world, whether Claude sits inside the product they sell or inside the way they design, test, and run their own hardware, working alongside them to 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 that accelerate their development, and understand their engineering workflows end to end, from design and simulation through test, production, and operations, so that your guidance fits how real hardware gets built
Develop prototypes and technical documentation, including evaluation suites, benchmarks grounded in real engineering tasks, AI engineering techniques, and architecture diagrams, that enable startups to build, operate, and scale with Claude
Create reference implementations and sample code that many companies can adopt without starting from scratch, 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, including what is hard about applying AI to physical systems such as reading drawings, 3D geometry, board layout and routing, GD&T, latency and on-premise constraints, and physical safety, then build repeatable evaluations and solutions and contribute insights back to Product, Engineering, Research, and the broader Applied AI team
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
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, along with strong opinions of your own about how to bridge the gap between what AI can do today and how physical things get built
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, 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 a love of working with founders and small teams that move quickly
Strong technical communication skills, with the ability to translate complex AI concepts into architectural decisions and actionable implementation plans for both software and hardware engineering audiences and to run technical workshops, hackathons, or developer-focused events
A collaborative approach to working across teams, the range of a generalist who can context-switch from robots to chips to rockets to factories and get up to speed on a new domain quickly, and a passion for making powerful technology safe and beneficial
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
