Recruiting Solutions Engineer
Embedded technical advisor to Anthropic's Recruiting team, leading education, hands-on support, and rapid prototyping of LLM-powered hiring workflows using Claude. Requires production LLM engineering experience, strong teaching skills for non-technical audiences, and pragmatic internal tooling development.
About the job
Key Responsibilities
- Serve as the dedicated technical advisor to the Recruiting organization — embedded with recruiters, sourcers, and coordinators to expand what's possible with Claude in real hiring workflows.
- Lead with education: identify and codify the skills and workarounds recruiters have created, turn them into teachable and reusable assets, and run the enablement motion (sessions, office hours, workshops) that scales them across the org.
- Work hands-on with recruiters: pairing on prompts, skills, and agent workflows; debugging where things break; turning support patterns into documentation so the same question isn't answered twice.
- Develop fast prototypes and pilots for high-value workflows that education alone can't solve — built scrappy, validated with real recruiter usage, and designed from day one with a graduation path into People Products' production stack.
- Collaborate closely with our internal AI governance group (the AI Council) to vet recruiter-built skills into shared tooling, and with People Products to hand off pilots that earn productionization.
- Identify patterns across teams and engagements, and contribute insights back to Recruiting leadership, Data Solutions, and People Products.
- Create technical content for recruiting audiences: documentation, tutorials, sample skills, and walkthroughs that assume curiosity rather than an engineering background.
- Foster community engagement through internal hackathons, demo sessions, and technical office hours.
Minimum Qualifications
- Experience as a Software Engineer, Forward Deployed Engineer, Solutions Engineer, or in a technical enablement role — or equivalent builder credibility from shipping real products.
- Production experience building LLM-powered applications and workflows, including prompting, context engineering, agent architectures, and evaluation.
- Strong programming skills (e.g., Python, TypeScript) and a pragmatic approach to internal tooling — you'd rather ship a working pilot this week than architect for a year.
- Genuine enthusiasm for teaching audiences without engineering backgrounds: you can translate AI concepts into language and habits that stick, and you measure success by what people can do without you.
- The judgment to know when a problem needs enablement, when it needs support, and when it needs software — and the discipline not to build when teaching will do.
- Strong communication skills that earn trust with both recruiters and engineers.
- Passion for making powerful technology safe and beneficial.
Preferred Qualifications
- Experience with recruiting or people technology (Greenhouse, Workday, scheduling and sourcing tools).
- Experience working inside or alongside recruiting, people operations, or another operations-heavy function.
- A track record of internal-tools or platform work where the customer sat next to you.
- Experience running enablement programs, workshops, or developer relations-style motions.
Compensation
Annual Salary: $270,000—$290,000 USD
Education
- 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.
Skills
Llm-Powered Applications, Prompting, Context Engineering, Agent Architectures, Evaluation, Python, TypeScript, Claude, Greenhouse, Workday
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