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Manager of Applied AI Architecture, Commercial

Anthropic · San Francisco, CA | New York City, NY

Location
San Francisco, CA | New York City, NY
Salary
$315,000 - $380,000 USD
Experience
7+ years
Funding
$15.3B
Posted
Aug 20, 2026

Anthropic is hiring a Manager of Applied AI Architecture, Commercial based in San Francisco, CA | New York City, NY. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.

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Role details

About Anthropic 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 the Manager of Commercial Applied AI Architects at Anthropic, you will drive adoption of frontier AI across our mid-market and SMB customers by leading a team of technical architects who help companies build and deploy with the Claude API, Claude Code, the Agent SDK, and Claude for Enterprise. Commercial is one of Anthropic's largest and fastest-moving books of business: thousands of companies, a rapidly growing sales team, and a small group of architects whose job is to change deal outcomes where technical depth matters most. Your team's leverage does not come from being everywhere. It comes from choosing the right accounts to go deep on, then turning what they learn there into blueprints, demos, tooling, and enablement that reach the rest of the book. You will bring your own builder credibility and technical judgment to the role. Our architects ship working code: prototypes, eval frameworks, near-production examples that customers extend, and internal tooling that scales the team itself. You do not need to be the strongest engineer in the room, but you should expect to be in the work with your team, not just reviewing it from above. When an architect is deep in a hard engagement, you will often be right there alongside them, unblocking, pairing, and pressure-testing, while the account itself stays theirs. This is a first-line leadership role reporting to the Head of Applied AI, Commercial. You will start by managing a team of architects and are expected to help grow it well beyond its current size, partnering with Commercial sales leadership on coverage, qualification, and where technical investment pays off. You will co-own the strategy for how Applied AI shows up in the Commercial segment, and you will be judged on your team's outcomes and growth, not your own. Responsibilities: Manage, coach, and grow a team of Commercial Applied AI Architects, setting a high bar for technical credibility, customer impact, and speed Own hiring for your team as it scales, defining the profile, running the loop, and building onboarding that gets new architects into customer conversations quickly Set goals and run reviews for your team, and develop each architect's career with clear, direct feedback Decide where your team's depth goes. Own the qualification and prioritization framework for Applied AI engagement across a very large book, and be comfortable saying no Work alongside your architects on their most consequential engagements, from technical discovery through deployment and expansion, and model what great looks like without taking the work off their plate Build and own the segment's technical playbooks for Claude API integrations, Claude Code rollouts, agentic architectures on the Agent SDK, and Claude for Enterprise deployments, and turn account-level wins into reusable assets that scale one-to-many Partner closely with Commercial sales leadership and Account Executives to co-build segment strategy, tighten the AE-to-architect operating model, and drive adoption across mid-market and SMB Ensure your team consistently surfaces how mid-market companies are building with Claude, and translate that signal into actionable feedback for Product and Engineering Represent Anthropic technically at customer sites, workshops, roadshows, and events, and contribute to thought leadership through content and speaking Stay ahead of the AI engineering landscape, including agentic architectures, eval design, context engineering, and developer tooling, and keep your team operating at the frontier You may be a good fit if you: Have 7+ years of experience in technical customer-facing roles (Solutions Architect, Sales Engineer, Forward Deployed Engineer, or similar), with 3+ years managing pre-sales or technical go-to-market teams Know how to hire well, coach effectively, give hard feedback kindly, and create an environment where builders do their best work Have led technical teams in a high-velocity, high-volume sales motion, where the constraint is your team's capacity rather than pipeline, and have a real point of view on how to allocate scarce technical talent across a large book Bring builder credibility. You have built and deployed LLM-powered applications, you understand what separates a prototype from a production system, and you can hold your own with a customer's engineering leadership Have hands-on familiarity with agentic architectures, LLM evaluation, and modern AI developer tooling, and can coach architects through the design decisions their customers face Have a systems mindset. When you see a problem, your instinct is to build one thing that serves ten customers rather than ten things that serve one Are comfortable in ambiguous, early-stage environments where the playbook does not exist yet, and have a track record of building structure as you go Have strong executive presence and can build trust with technical and business leaders alike Have a genuine passion for making powerful technology safe and societally beneficial Strong candidate may have: Scaled a technical pre-sales or forward-deployed team from a handful of people to a mature function, including defining the hiring bar, onboarding programs, and coaching systems from scratch Sold to and built for mid-market companies, with a clear understanding of how technical buying decisions differ between a 500-person company and a Fortune 500 Rolled out AI coding assistants or developer tools inside engineering organizations, and know how those teams evaluate, adopt, and measure them A visible technical presence through conference talks, written content, or open-source contributions The annual compensa

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