Senior Partner Systems Analyst

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 Our Partner Experience team is building an AI-native operating model on top of a growing set of partner-facing systems: Salesforce, PEM, the partner portal, enablement and certification platforms, and the integrations that connect them. Our systems lead owns the architecture and data model. Our GTM Systems team builds and releases changes in Salesforce. Our AI Operations Engineer builds the agentic workflows that run on top of it. This role connects the business to all of them: a senior business systems analyst who runs discovery, captures requirements, leads UAT, and publishes release notes for every bug fix, improvement, enhancement, and new build, and who is hands-on enough as a Salesforce admin to keep the platform healthy in production. You'll use Claude every day to draft requirements, write test cases and release notes, and keep documentation current, and you'll be the person who spots which recurring requests should become automations. As our Senior Partner Systems Analyst, you'll own how change happens on the partner systems stack. When a partner program launches, a partner manager needs a new workflow, or a partner can't see their deal registration, you're the first call. You'll sit down with the people who raised it to understand the problem, write requirements the GTM Systems team or the AI Operations Engineer can build from, run UAT with the people who will use it, and publish release notes so nobody has to ask what changed. For smaller fixes, you'll make the change yourself as a Salesforce admin. This is a senior analyst role with real ownership. You'll set up the intake, discovery, UAT, and release processes rather than inherit them, decide what gets worked on first, and make sure nothing ships without agreed requirements, UAT sign-off, and release notes. Key responsibilities • Lead discovery for new requests: meet with partner managers, partner operations, and other stakeholders to understand the problem, map the current process, and size the change before anything is built. • Capture requirements for bug fixes, improvements, enhancements, and new builds: user stories, process flows, field and access definitions, acceptance criteria, and edge cases, precise enough that the systems lead, the GTM Systems team, the AI Operations Engineer, or an implementation partner can build from them. • Work with the GTM Systems team and the AI Operations Engineer through the full delivery cycle for enhancements, improvements, new builds, and bug fixes: hand over requirements, answer questions during the build, review what was built against the acceptance criteria, and coordinate the release. • Own UAT for every change: write the test plan and test cases from the acceptance criteria, coordinate testers from the partner team, log and retest defects, collect sign-off, and smoke test in production after each release. • Write and publish release notes for every release: what changed, who it affects, and what users need to do differently, in language partner managers can act on. • Prioritize the backlog with stakeholders, weighing partner impact, risk, and effort, and keep a clear, visible view of what's coming next and why. • Serve as the point of contact for bugs, enhancement requests, and system questions across Salesforce, PEM, and the partner portal, and own the intake queue end to end. • Triage production incidents: reproduce the issue, assess impact and severity, resolve it or route it to the right owner, and keep affected teams updated until it's closed. • Administer Salesforce for the partner org: objects, fields, page layouts, validation rules, flows, permission sets, reports, and dashboards. • Understand how data moves between Salesforce and PEM, monitor integration health, and diagnose sync failures, mapping errors, and access issues. • Document the platform: system documentation, data dictionary, integration maps, and admin runbooks. • Identify repeatable admin and support requests, log them as automation candidates, and partner with the AI Operations Engineer to move them off the manual queue. Minimum qualifications • Experience running discovery and requirements sessions with business stakeholders, and turning what you hear into user stories, process flows, and acceptance criteria. • A track record of working with a systems or engineering team through a build, from requirements handover to release. • Disciplined testing habits: you have planned and run UAT with business users, with test cases written from acceptance criteria, defects tracked to closure, and sign-off before release, and you don't consider a change done until it has been smoke tested. • Clear written communication: your requirements get built correctly the first time, your release notes tell non-technical users what changed and what to do, and your documentation is something people actually use. • You already use LLM tools like Claude in your day-to-day work and can show where it changed how you gather requirements, test, or document. • A track record of owning a production Salesforce org or business systems stack, including the intake, triage, and release processes around it. • Strong Salesforce admin skills: declarative configuration, flows, validation rules, the security and sharing model, and reporting. • Working knowledge of integrations: how records sync between systems through APIs or middleware, how to read an error log, and how to trace a data issue back to its source. • A structured approach to incidents: you separate symptoms from root cause and communicate clearly while things are broken. • Judgment about priorities: you can sa