Manager of Applied AI Architecture, Startups

Manager of Startups Applied AI Architects

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. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role:

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.

This is a role for a proven technical go-to-market leader who knows how to build teams that move at startup speed, earn the trust of deeply technical buyers, and turn a scrappy early engagement into a lasting technical partnership. You'll define the playbooks for nurturing and scaling new customers, set the bar for technical excellence, and grow the people — while staying close enough to the ground to know what's actually working. You will partner with the New Business sales leader and work as one team to support your customers.

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

You May Be A Good Fit If You:

• 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

Strong Candidates May Have:

• 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

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary: $315,000 —$380,000 USD

Logistics

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

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

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