Manager

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.

• Build, coach, and grow a team of Applied AI Engineers serving Mega accounts
• Staff engineers into account-aligned pods alongside Applied AI Architects
• Set performance goals aligned with each Mega's technical account plan
• Serve as a senior technical advisor to Mega product and engineering leaders
• Lead hands-on co-build initiatives with Mega engineering teams
• Help navigate the partner-customer duality
• Act as a technical escalation point for your team's accounts
• Build shared assets across pods, including reference architectures, agentic patterns, and eval frameworks
• Collaborate with Product and Research to surface Mega-driven requirements
• Champion scalable public and internal assets documenting the latest LLM prompting, evaluation, agentic, and architecture techniques
• Maintain strong, current knowledge of LLM capabilities, implementation patterns, and the AI product development stack
• Travel to customer sites for workshops, executive technical sessions, implementation support, and relationship building

• 6+ years of experience in technical roles such as Forward Deployed Engineer, Software Engineer, Solutions/Sales Engineer, or Technical Product Manager
• 4+ years of experience operating in a formal leadership capacity, ideally with some tenure as a manager of managers/multiple teams
• Demonstrated success hiring, coaching, and scaling customer-facing technical teams
• Experience supporting large, named strategic accounts at a platform, infrastructure, or model company
• Production experience with LLMs, including advanced prompt engineering, agent development and frameworks, evaluation frameworks, transcript analysis, MCP, and deployment at scale
• Strong programming skills with proficiency in Python or TypeScript and experience building production applications
• A track record engaging senior technical stakeholders (CTOs, CPOs, and engineering leaders)
• Experience working in or running mixed pre-sales and hands-on engineering teams
• The ability to navigate ambiguity and execute across domains with intellectual openness