About the job
As a Manager of Startups Applied AI Architects at Anthropic, you will drive adoption of frontier AI by leading a team of technical architects to help startups build AI-native products with the Claude Developer Platform. Your team is expected to win the trust of founders and engineers by supporting their technical ambitions from early product to scale. You'll bring your own builder credibility and startup instincts to the role — setting the vision for what great technical partnership looks like in the startup segment, developing a high-performing team, and personally carrying relationships with Anthropic's most strategic early-stage accounts.
Responsibilities
Lead, develop, and grow a team of Startups Applied AI Architects — setting a high bar for technical credibility, customer impact, and startup-paced execution
Drive team performance through clear goal-setting, regular coaching, and a culture of continuous technical development
Personally lead pre-sales engagements with high-priority startup accounts, from initial technical discovery through deployment and expansion, modeling what great looks like for your team
Build and own the segment's technical playbooks: how to run technical evaluations, develop customer-specific eval frameworks, architect LLM solutions for resource-constrained early-stage teams, and win against competitive alternatives
Partner with aligned Account Executives and GTM leadership to shape segment strategy and drive Claude API adoption across the startup ecosystem
Ensure your team consistently surfaces insights on how startups are building with Claude — emerging use cases, deployment patterns, architectural decisions — and translate that signal into actionable feedback for Product and Engineering
Drive cross-functional influence across Sales, Product, and Engineering to advance startup customer needs and shape roadmap priorities
Build Anthropic's technical presence and credibility in the startup ecosystem through events, conferences, workshops, and content
Stay ahead of the AI engineering landscape — context engineering, eval frameworks, agentic architectures, developer tooling — and ensure your team is operating at the frontier
Qualifications
Minimum
Have 8+ years of experience in technical customer-facing roles (Solutions Architect, Sales Engineer, Forward Deployed Engineer, or similar), with 5+ years leading and managing pre-sales or technical go-to-market teams
Have a strong track record of building and developing high-performing SA teams — you know how to hire well, coach effectively, and create an environment where technical talent grows and does their best work
Have deep experience working with startups or high-growth technology companies — you understand the velocity, constraints, and culture of early-stage companies and know how technical decisions get made at each stage of the journey
Bring genuine builder credibility: you've built and deployed LLM-powered applications, you speak the language of founders and founding engineers, and you can earn the trust of deeply technical audiences without relying on a title
Have hands-on expertise with context engineering, LLM evaluation frameworks, and modern AI architectures, and can guide both your team and customers through the decisions that separate a prototype from a production-grade system
Are comfortable with Python and fluent in the LLM frameworks, tools, and integration patterns common in startup engineering stacks
Are energized by building in ambiguous environments — you're excited to define the playbook, not just run it, and you thrive in fast-moving contexts where the technology and the customer segment are both evolving rapidly
Have a genuine passion for making powerful technology safe and societally beneficial
Preferred
Experience as a technical founder or in a founder-led sales motion, giving you firsthand understanding of what technical buyers in the startup world are actually evaluating
A track record of winning competitive technical evaluations against other LLM providers
Experience building foundational team infrastructure from the ground up: hiring frameworks, onboarding programs, technical playbooks, and coaching systems in a high-growth environment
Deep familiarity with how developer infrastructure procurement evolves from seed through Series B and beyond, and how to adapt your team's approach accordingly
A visible technical presence in the startup or AI engineering community through conference talks, written content, or open-source contributions