Staff+ Software Engineer, Enterprise Connectivity

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.

A connected Claude is the difference between a general-purpose chatbot and a real coworker. We're building the connected enterprise on three fronts: zero-touch activation, a thriving connector ecosystem, and an enterprise control plane that lets organizations adopt with confidence. We own the path from discovering a connector to using it every day: default and suggested connectors, one-click setup, connector requests, and the identity and admin pieces that remove setup friction for a whole organization at once.

You'll be a technical leader who owns activation end to end, from the moment someone sees a connector to their first successful use of it. You'll also help to shape the foundations that help the connector ecosystem grow, and the governance controls that make it safe at enterprise scale. You'll partner closely with product, design and data science, and carry real ownership over what we ship next.

Minimum Qualifications

• Own connector activation end to end: measure the funnel from discovery to first use to habit, find the biggest drop-offs, and fix them
• Build and run experiments on default connectors, in-product suggestions, connector requests and onboarding flows
• Make setup close to zero-touch, building on open standards like Cross App Access (XAA) and the MCP authorization spec so one approval can turn a connector on for everyone
• Improve the connectors people reach for most, like Microsoft 365 and Google Workspace, so the first experience works and keeps working
• Lay platform foundations for the connector ecosystem: reusable building blocks that make every new connector easier to launch, discover and activate
• Build out the enterprise control plane: admin controls and governance (domain restrictions, labels, permissions) that help security teams say yes faster instead of blocking rollout
• Partner with product, design, data science and sales to turn usage data and customer feedback into priorities
• Set technical direction and standards for the team, mentor other engineers, and lead with influence rather than authority
• Have shipped growth or activation work: onboarding flows, funnels, experimentation, and measuring what actually moves usage
• Are comfortable with authorization and identity (OAuth 2.0, OIDC, SSO), enough to make setup flows simple without cutting corners
• Have built on large platform APIs (Microsoft Graph, Google Workspace or similar) and can debug failures on both sides of the boundary
• Have built platform or ecosystem surfaces that other teams or developers rely on, and care about durable, well-designed APIs
• Understand what enterprise admins and security teams need from policy, permissions and governance at scale
• Use data and user research to decide what to build, and can explain the tradeoffs to product and design partners
• Drive cross-team and cross-company alignment to ship, with influence over authority

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.

• Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level
• Contributed to or implemented emerging auth standards (IETF OAuth drafts, MCP authorization)
• Experience with data governance or information protection (sensitivity labels, DLP)
• Built admin consoles or policy engines for multi-tenant SaaS

$405,000—$485,000 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.