Senior Partner Systems Analyst - Salesforce & AI Ops

WinsAbove

San Francisco (CA)

Hybrid

USD 215,000 - 300,000

Full time

7 days ago

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Job summary

Anthropic is seeking a Senior Partner Systems Analyst to own how changes occur on the partner systems stack. You will run discovery, capture requirements, lead UAT, and publish release notes, with hands-on Salesforce admin capabilities for production health.

You will draft requirements for automation and coordinate across GTM Systems and AI Operations Engineer teams to deliver impactful improvements. You will work with partner managers, operations, and other stakeholders to ensure clear

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 say "no" or "not yet" and explain why.

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.