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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.

We're seeking an experienced software engineer to build the platform behind governance, risk, and compliance (GRC) at Anthropic. Compliance information lives across dozens of systems, from cloud infrastructure and identity providers to HR platforms and code repositories. You'll build the pipelines, integrations, and services that bring that data together and turn it into automated checks, real-time dashboards, and evidence for real time decision making, compliance obligations, and to support expanding the markets we can serve.

You will be an early member of the team, collaborating with stakeholders across Security, IT, Engineering, Privacy Engineering, Legal, Finance, and more to turn manual compliance processes into scalable, reliable systems. You will lead your own projects end to end, and you will put Claude to work as an extension of the team through agentic workflows for evidence collection, analysis, and continuous monitoring. If you've built internal platforms, data pipelines, or privacy systems, you'll feel right at home, and you don't need a compliance background to get started.

• Design and build data pipelines that aggregate risk, control, and asset information from across Anthropic's technology stack, solving hard integration problems like disparate schemas, inconsistent data quality, and unified views of posture
• Build and maintain integrations connecting our platform to cloud infrastructure, identity management, HRIS, ticketing, version control, and CI/CD systems to enable automated evidence collection and continuous validation
• Translate written policies and regulatory requirements into policy-as-code, turning static documents and spreadsheets into enforceable rules, automated checks, and continuous monitoring
• Design and deploy agentic workflows where Claude handles work that previously required manual effort, such as analyzing evidence, generating audit responses, and monitoring control effectiveness
• Develop dashboards and reporting that provide real-time visibility into risk and compliance posture for audiences ranging from engineers to executives and external auditors
• Make architectural decisions that shape how the platform grows, establishing patterns and tooling that other engineers will build on
• Partner with Security, IT, Infrastructure, and product engineering teams to make controls and evidence collection native to how Anthropic builds and ships
• Operate what you build, owning reliability and data integrity for systems that audits and executive reporting depend on

• Have 8+ years of experience building backend systems, data pipelines, or internal platforms that other teams depend on, ideally operating at tech lead level
• Are a systems thinker who understands how data flows between systems, where the integration points are, and what breaks when systems don't talk to each other
• Have depth in either integration engineering (REST APIs, webhooks, authentication flows, event-driven architectures) or data infrastructure (warehousing, ELT/ETL, orchestration), and fluency in the other
• Are proficient in Python, Go, or similar languages, and have production experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code
• Hold a high bar for data quality and reliability, and enjoy turning ambiguous, manual processes into simple, reliable automated systems
• Take full ownership of your work, from design through deployment and operations, and can navigate ambiguity and make sound technical decisions independently
• Take a product-focused approach to platform work and care about building tools internal customers love to use
• Are excited to build with LLMs as system components, designing agentic workflows, evaluating their outputs, and making them reliable enough for high-stakes use

• Experience in domains where engineering meets regulation, such as privacy engineering, data governance, fintech, healthcare, or trust and safety
• Experience designing and shipping LLM-based or agentic automation in production or operational contexts
• Familiarity with compliance frameworks (SOC 2, ISO 27001, HIPAA, FedRAMP) or GRC platforms (ServiceNow, Vanta, Drata, OneTrust); this is helpful but not required
• Prior experience at high-growth startups, building processes and systems that scale

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.

Annual Salary: $405,000 —$405,000 USD

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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

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.

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.