AI Operations Engineer, Partnerships

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

Our Partner Experience team is building an AI-native operating model. We already run a growing set of partner-facing systems: a partner portal, CRM workflows, enablement and certification platforms, and the trackers that connect them. The systems lead on our team owns that foundation — the portal, the data model, and the integrations that keep partner records accurate and flowing.

This role is the other half of that build. As our AI Operations Engineer, you'll design, build, and run the agentic workflows that sit on top of those systems: Claude-powered agents and automations that triage partner applications, draft and send partner communications, sync data across tools, surface deal and enablement signals, and take routine operational work off the team entirely. Where the systems lead builds the rails, you build what runs on them.

This is a builder role, not an analyst role. You'll ship working automations weekly, own them in production, and continuously expand what the team can do without adding headcount.

Key responsibilities:

• Design and build agentic workflows (using Claude, MCP connectors, and API integrations) that automate core partner experience operations: application triage, onboarding, deal registration, certification tracking, partner communications, and reporting
• Partner closely with our systems lead to integrate these workflows with the partner portal, CRM, enablement stack, finance systems, and database systems — consuming and writing back to the systems of record rather than creating shadow processes
• Turn recurring manual work into reliable, monitored automations: define the workflow, build it, test it against real cases, add guardrails and human-in-the-loop checkpoints where decisions carry risk, and document how it runs
• Own the operational health of what you ship: error handling, edge cases, escalation paths, and iteration when partner processes change
• Prototype fast with the team: sit with partner managers, find the highest-friction workflows, and get a working v1 in front of them in days, not quarters
• Establish reusable patterns (skills, prompts, connectors, playbooks) so each new workflow is faster to build than the last, and teach the broader team to self-serve on the simple ones
• Hands‑on experience building with LLMs and agentic tooling: prompt and workflow design, tool/function calling, MCP or comparable integration frameworks, and evaluating agent output quality
• Strong judgment about automation risk: knowing which steps an agent can own outright, which need a human checkpoint, and how to design for graceful failure
• Process instincts: ability to look at a messy manual workflow, find the actual bottleneck, and redesign it rather than just automating it as‑is
• Clear written communication; documents what you build so it outlives you

Preferred qualifications:

• 5+ years in operations engineering, solutions engineering, business systems, RevOps, or a similar build‑heavy role, ideally supporting a partner, sales, or customer success organization
• Experience in partner/channel operations specifically (deal registration, MDF/co‑sell programs, partner tiering, certification pipelines)
• Experience shipping internal AI tools or automations that are still running in production today
• Familiarity with the Claude API, Claude Code, or agent frameworks; building custom MCP servers is a plus

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.

$215,000 - $300,000 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.

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.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit‑Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

As set forth in Anthropic’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.