Engineering Manager, GRC Platform

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 We are seeking an Engineering Manager, GRC to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them. At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible. Key responsibilities · Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows. · Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools. · Inform GRC platform strategy and implementation: in partnership with other programs, plan for and build tooling that meets our compliance requirements. · Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents. · Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on. · Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information. · Design and maintain integrations connecting GRC tooling with cloud infrastructure, identity management systems, HRIS platforms, ticketing systems, version control, and CI/CD pipelines—working with engineers to implement integrations that enable automated evidence collection and continuous compliance validation. · Build and lead an AI-forward GRC engineering function as we scale: hiring team members, establishing practices, and defining the technical roadmap for governance and compliance automation at Anthropic. Minimum qualifications · Are a systems thinker first. You understand how complex environments work: how data flows between systems, where integration points exist, what breaks when systems don't talk to each other. You can both design the right architecture and environment for an enterprise-grade internal tool, as well as implement and iterate on that architecture as the organization and priorities evolve. · Have a relentless focus on data integration: you understand how to pull data from multiple sources, normalize it, join it meaningfully, and surface insights. You're comfortable reasoning about messy, inconsistent data and designing systems that handle edge cases gracefully. · Understand APIs and integration patterns: REST APIs, webhooks, authentication flows, polling vs. push architectures, and can evaluate systems based on how well they expose data and support automation. · Can work independently with minimal guidance, taking ownership of complex problems from design through implementation while managing ambiguity inherent in early-stage programs. · Have strong analytical and problem-solving skills with attention to detail necessary for compliance work, balanced with pragmatism about risk-based prioritization in fast-paced environments. · Familiarity with cloud platforms (AWS, GCP, Azure) and an understanding of how compliance-relevant data can be extracted from their APIs and logging systems. · Familiarity with Infrastructure as Code tools (Terraform, CloudFormation, Ansible) and DevSecOps practices including CI/CD pipeline integration and policy-as-code implementations. Preferred qualifications · Have 12+ years of total experience and 3-4+ years of experience managing technical individual contributors or systems-focused teams, with a proven track record of building or scaling small teams (2-5 people) in security, compliance, automation, or operations functions. · Have 5+ years of experience designing, building, and scaling automated workflows, data pipelines, or system integrations. · Balance strategic thinking with hands-on technical leadership: bring a full-stack mindset and do what it takes to solve problems end-to-end — building pipelines and integrations yourself while the team is small, and going deep on code and design reviews as it scales. · Have a strong technical foundation with proficiency in Python (or a similar language) for automation, API integration, and data transformation — you're comfortable writing, reviewing, and shipping production code alongside your team, and expect to stay close to the code as the team grows. · Experience designing or implementing AI-powered automation, agentic workflows, or LLM-based tooling in operational contexts. · Experience with GRC platforms such as ServiceNow GRC, Vanta, Drata, OneTrust, RSA Archer, or similar tools including configuration, customization, and integration capabilities. · Prior experience in high-growth startup environments demonstrating ability to build scalable processes and adapt quickly to changing requirements and priorities 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. Annual Salary: $320,000—$405,000 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 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.