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Salary: GBP 225,000 - 255,000 / annual
Anthropic's Beneficial Deployments team is seeking an Applied AI Engineer to join the Life Sciences group, based in London. The role focuses on deploying Claude to automate scientific research and laboratory workflows, helping labs close the loop on scientific discovery through AI-driven hardware and software integration.
You will work directly with research labs to automate experiments end-to-end using Claude, from initial advisory and prototyping through production deployment. A key responsibility is driving product, engineering, and research direction based on field experience—including building evaluations to measure model limitations in physical-world settings, developing new features for the Model Hardware Standard (MHS), and identifying safety considerations for AI in lab environments.
You'll scale impact across the long tail of labs by creating reusable cookbooks, documentation, and other assets that enable adoption without your direct involvement. As an EMEA ambassador for Claude in scientific contexts, you'll inspire and build trust with research audiences through both intimate technical engagements and large conference presentations. The role requires significant travel across Europe, Middle East, and Africa.
Key responsibilities include:
- Working with labs to automate experiments end-to-end with Claude, from advisory through production code
- Driving product, engineering, and research direction based on field learnings (e.g., building evals for model limitations, developing MHS features)
- Creating scalable, reusable assets for broader lab adoption
- Serving as technical ambassador and building researcher trust across EMEA
- Significant travel as part of the role
Requirements:
- Hands-on experience connecting software to lab robots and instruments (liquid handlers, plate readers, scheduling software, LIMS), ideally in an automated lab setting
- Strong engineering skills: ability to take LLM-powered tools from prototype to production code and write evals to measure performance
- Scientific intuition for experiment design: ability to identify automation opportunities and recognize where AI might fail or pose safety risks in physical systems
- Experience working directly with external customers or partners in a technical capacity
- Clear written and verbal communication skills; ability to write documentation for independent use and deliver talks that inspire researcher confidence
- Scrappy, adaptable mindset: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and prioritizing mission impact
- Bachelor's degree or equivalent combination of education, training, and professional experience in a field relevant to the role
- Years of experience will correlate with internal job level requirements
