Full-Time

Partner Business Systems & AI Operations Lead

Anthropic

Anthropic

5,001-10,000 employees

Develops reliable, interpretable AI systems

Compensation Overview

$215k - $300k/yr

H1B Sponsorship Available

San Francisco, CA, USA

Hybrid

Must be in office at least 25% of time.

Category
Business & Strategy (2)
,
Required Skills
LLM
Claude
Salesforce
n8n
Zapier
Requirements
  • Have five or more years in revenue systems, partner systems, or business systems roles with hands-on Salesforce administration or architecture experience.
  • Have owned a data model that other teams depended on and understand what it takes to keep a shared source of truth reliable.
  • Can translate a program rule into a schema, a validation rule, and an entitlement flow without a detailed specification.
  • Have integrated Salesforce with at least one learning management system, partner relationship management, or partner portal product.
  • Work well in high-ambiguity, high-ownership environments and bias toward shipping over perfecting.
  • Have hands-on experience building with large language models or AI agents — prompt engineering, evals, agentic workflows, or wiring an LLM into a production process — and treat AI as a tool to deploy, not a topic to discuss.
  • Are fluent with workflow automation tools (Zapier, n8n, Workato, Make, or similar) and can stitch systems together without waiting for engineering.
Responsibilities
  • Work with the Revenue Systems team on the Salesforce partner data model end to end, including the Account object schema, custom fields, picklist governance, validation rules, and record types. Work in close coordination with Revenue Operations and Enterprise Systems, who own and maintain the Salesforce org, to manage change on partner-specific objects within that shared environment.
  • Administer the partner platform stack, including the partner portal, partner dashboards, and the access and entitlement layer that determines what partners see based on tier and status.
  • Define and own the partner data quality standard. Establish completeness and accuracy checks, build the monitoring, and run remediation so that Partner Strategy and Operations receives a clean, documented dataset on a defined cadence. Partner Strategy and Operations owns the warehouse, BI layer, and executive reporting; this role guarantees the source they build on.
  • Partner with the Business Process Manager to instrument every partner process so that process health is queryable, including cycle times, queue depth, and SLA adherence. They design the process; this role makes it executable and measurable in tooling.
  • Run access and configuration governance for partner systems, including change management on the partner object, sandbox-to-production discipline, and permission-set hygiene, working with Legal and Security on portal access governance and partner data handling requirements.
  • Build and operate the AI automation layer across the partner workflow stack — agentic workflows, LLM-driven triage and drafting, automated QA, and Claude-powered internal tooling — to absorb operational work that would otherwise require additional headcount.
  • Identify high-volume, judgment-heavy partner ops work (application screening, support triage, comms drafting, data hygiene) and convert it into AI-augmented or fully automated processes, measured by cycle-time and human-touch reduction.
  • Set the bar for how the partner systems org uses AI internally, including evals, guardrails, and reviews, so that automation gets shipped responsibly and the failure modes are understood before they reach a partner.
Desired Qualifications
  • Salesforce Administrator or Platform App Builder certification, or experience with Experience Cloud or a Partner Relationship Management such as Impartner or Salesforce Partner Relationship Management.
  • SQL fluency for data quality checks and ad hoc analysis.
  • Prior partner program or channel operations experience.
  • Experience standing up a data quality program from the ground up.
  • Shipped an AI-powered or LLM-driven workflow into a production ops environment — bonus if it replaced meaningful human work.
  • A working point of view on where AI helps and where it doesn't in business operations, informed by hands-on experimentation rather than theory.

Anthropic focuses on AI research to build reliable, interpretable, and steerable AI systems. Its main product, Claude, is an AI assistant designed to handle tasks at any scale for clients across industries, delivered through deployment and licensing along with specialized AI R&D services. Claude works by combining natural language processing, human feedback, reinforcement learning, and interpretability techniques to produce a capable, controllable AI assistant that can assist with a wide range of tasks. The company differentiates itself from competitors by prioritizing safety, transparency, and controllability—emphasizing reliability, interpretability of model behavior, and user-controlled steerability in its AI systems. Anthropic’s goal is to make AI systems that people can trust and efficiently use to improve operations and decision-making across sectors.

Company Size

5,001-10,000

Company Stage

Late Stage VC

Total Funding

$77.3B

Headquarters

San Francisco, California

Founded

2021

Simplify Jobs

Simplify's Take

What believers are saying

  • Claude for Small Business targets 36M US firms via QuickBooks and Canva integrations.
  • Japan's three megabanks access Claude Mythos by May 2026 end, expanding finance revenue.
  • Thomson Reuters MCP links Claude to 1.9B Westlaw documents for legal dominance.

What critics are saying

  • Japan FSA's 36-entity group imposes Mythos cybersecurity audits within 6 months.
  • Legal hallucinations trigger malpractice suits against Freshfields using Claude live.
  • Thomson Reuters captures enterprise legal revenue, sidelining Anthropic plugins.

What makes Anthropic unique

  • Anthropic prioritizes AI safety through interpretable and steerable Claude models.
  • Claude integrates Model Context Protocol for grounded legal and business workflows.
  • Constitutional AI framework ensures Claude aligns with human values and transparency.

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Benefits

Flexible Work Hours

Paid Vacation

Parental Leave

Hybrid Work Options

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

-3%

1 year growth

-3%

2 year growth

1%
Ars Technica
Apr 21st, 2026
Mozilla: Anthropic's Mythos AI model finds 271 zero-day bugs in Firefox 150

Mozilla has discovered 271 security vulnerabilities in Firefox 150 using early access to Anthropic's Mythos Preview AI model. The findings represent a significant increase from the 22 bugs detected by Anthropic's Opus 4.6 model in Firefox 148 last month. Firefox CTO Bobby Holley said Mythos is "every bit as capable" as the world's best security researchers, whilst eliminating the need to "concentrate many months of costly human effort to find a single bug". He believes AI tools like Mythos tilt the cybersecurity balance towards defenders by making vulnerability discovery cheaper. Anthropic released Mythos Preview to a limited group of industry partners earlier this month. Mozilla CTO Raffi Krikorian argues such tools are particularly crucial for open source projects, which often rely on insufficient volunteer maintenance for security.

Bloomberg L.P.
Apr 21st, 2026
Anthropic's Mythos AI sparks fear and hope over cybersecurity threats to global finance

Anthropic's new AI model Mythos has sparked concern amongst policymakers at International Monetary Fund meetings over its potential to accelerate sophisticated cyberattacks on the global financial system. However, its developers argue the technology could provide banks with their strongest defence yet. What distinguishes Mythos is its ability to chain multiple security weaknesses into coordinated attacks, effectively automating complex cyber intrusions. This capability could significantly expand the pool of potential attackers in the near term. The model's creators emphasise a longer-term benefit: the same technology could enable banks to detect and patch vulnerabilities faster than ever, potentially shifting the balance towards defenders if widely adopted. The dual-use nature of Mythos has created both panic and optimism in boardrooms and governments regarding global financial system security.

Bloomberg L.P.
Apr 17th, 2026
Indian fintechs push Anthropic for early access to 'dangerous' Mythos AI model

Indian fintech companies including One97 Communications, Razorpay Software and Pine Labs are pushing Anthropic for early access to Mythos, the AI model that has raised global concerns about cyberattack risks. The firms want to test Mythos on their own systems to detect vulnerabilities following Anthropic's announcement of a limited rollout. The San Francisco-based AI developer considers the model too dangerous for wider release but major Indian financial technology companies are seeking early access to assess potential security threats to their platforms.

Bloomberg L.P.
Apr 16th, 2026
US government prepares to give federal agencies access to Anthropic's Mythos AI model

The US government is preparing to provide major federal agencies with access to Anthropic's new AI model, Mythos, according to a memo reviewed by Bloomberg News. Gregory Barbaccia, federal chief information officer at the White House Office of Management and Budget, informed Cabinet department officials on Tuesday that OMB is establishing protections to enable agencies to use the closely guarded AI tool. The move comes amid concerns that the powerful model could significantly increase cybersecurity risks. OMB is working to set up appropriate safeguards before rolling out access to the system across government departments.

Bloomberg L.P.
Apr 16th, 2026
Anthropic's Mythos AI model raises cybersecurity alarms for banks and governments

Anthropic's new Mythos AI model is causing concern among banks, tech giants and governments over its potential implications for cybersecurity and the internet's future. The model has prompted a scramble amongst major institutions to understand its capabilities and risks. Details about the specific features raising alarms were not disclosed in the source material.