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About the Role
Anthropic's Business Technology Engineering team builds and manages the company's internal systems, including employee platforms and collaboration tools. Engineers are embedded within business functions to leverage Claude AI, aiming to make Anthropic the best-run company in its use of AI internally and serve as a customer example. This role leads a growing engineering organization focused on Platforms and Forward Deployed engineering, shaping the future of internal AI deployment.
Responsibilities
- Lead and scale a global engineering organization, including hiring, leveling, and developing direct reports.
- Partner on developing and executing a roadmap for business functions' use of Claude and associated success metrics.
- Manage the Platforms track, ensuring reliability, velocity, and scale of Claude Support and the core employee platform.
- Oversee the Forward Deployed track, managing engagement portfolios, prioritization, handoffs, and adoption.
- Serve as the technical executive partner to leaders of Legal, Workplace, Comms, Product Ops, and Product Support.
- Collaborate with Labs and Product on dogfooding, providing feedback on evaluations and shipping internal builds that inform external product patterns.
- Represent Anthropic's internal operations to Enterprise customers in conjunction with GTM.
- Set the engineering standard for production-adjacent builds, evaluation rigor, reusable patterns, and responsible internal deployment with real data and permissions.
Requirements
- 12+ years in software engineering with 6+ years in engineering leadership.
- At least 3 years managing managers.
- Experience leading an organization of 20+ engineers across multiple domains structured by the candidate.
- Experience running internal-tools, business-systems, or platform engineering at a company that scaled functions faster than headcount.
- Demonstrated ability to speak to platform reliability and embedded adoption outcomes.
- Strong technical judgment, capable of discussing agent architecture, eval design, and failure modes.
- Ability to communicate trade-offs, make recommendations, and drive decisions with diverse stakeholders.
- Capacity to maintain high craft standards while declining low-leverage work.
- Desire for ownership in running a frontier AI lab's operations using its own models responsibly.
- Experience with corporate systems (Salesforce, Workday, Google Workspace, Slack) at scale is a plus.
- Experience building career rubrics or leveling frameworks for new engineering roles, or establishing a forward-deployed function from scratch is a plus.
- Forward deployed, software engineering, or applied AI leadership experience with external customers is a plus.
- Product management experience or a track record of close partnership with PMs and analysts is a plus.
Skills
- Software Engineering Leadership
- People Management
- Roadmap Development
- Platform Engineering
- Internal Tools Development
- Business Systems Engineering
- Technical Judgment
- Stakeholder Management
- Communication
- AI Deployment
- Evaluation Design
- Corporate Systems
- Product Management
Location
- San Francisco
Work Type
- Hybrid
Experience Level
- Senior Leadership
- 12+ years software engineering
- 6+ years engineering leadership
- 3+ years managing managers
Education Level
- Bachelor's degree or equivalent experience
Salary/Compensations
- $405,000—$485,000 USD
Benefits
- Competitive compensation
- Benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
- Office space for collaboration
- Visa sponsorship
About the Company
- Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.
- The team is a growing group of researchers, engineers, policy experts, and business leaders.
- Anthropic is a public benefit corporation headquartered in San Francisco.
- The company believes high-impact AI research is 'big science' and works as a cohesive team on large-scale research efforts.
- Values impact and advancing steerable, trustworthy AI.
- Views AI research as an empirical science.
- Highly collaborative group with frequent research discussions.
- Research directions include GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Equal Opportunity
- We encourage you to apply even if you do not believe you meet every single qualification.
- We think AI systems like the ones we're building have enormous social and ethical implications, making representation important.
- We strive to include a range of diverse perspectives on our team.