Product Manager, Agent Platform at ANTHROPIC PBC DBA ANTHROPIC INC

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Full Time

Start Date

Immediate

Expiry Date

12 Feb, 26

Salary

385000.0

Posted On

14 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Product Management, AI Safety, Technical Architecture, Data-Driven Decision Making, Stakeholder Engagement, Market Research, Go-To-Market Strategy, Analytical Thinking, Communication Skills, User Experience, Ecosystem Development, Developer Platforms, Infrastructure Products, Safety Evaluations, Evaluation Methodologies, Collaboration

Industry

Research Services

Description

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: As the Product Manager for Anthropic's Agent Platform, you'll own the strategic vision and execution for one of our most critical technology initiatives: building the foundational systems that enable AI agents to safely and effectively interact with the world. This role represents a unique opportunity to shape how frontier AI systems integrate with external tools, data sources, and environments while maintaining our unwavering commitment to AI safety. You'll work at the intersection of cutting-edge research and practical product development, translating breakthrough capabilities from our research teams into robust, scalable platforms that serve both internal needs and the broader AI ecosystem. Your work will directly impact how developers, enterprises, and end users interact with AI agents, setting the foundation for the next generation of human-AI collaboration. This is a high-impact role where you'll collaborate closely with Research, Engineering, Safety, and Go-to-Market teams to define and execute on a comprehensive agent platform strategy. You'll be responsible for driving product decisions that balance innovation velocity with safety requirements, user needs with technical constraints, and internal capabilities with external ecosystem development. Responsibilities: Own the end-to-end product strategy for Anthropic's agent platform, including agent infrastructure, skills, Model Context Protocol (MCP), and evaluation frameworks. Define and communicate a compelling product vision that aligns stakeholders across Research, Engineering, Safety, and Business teams on agent platform priorities Partner with Engineering leaders to ensure technical architecture decisions support long-term product goals and scale requirements, and deliver early access and research previews to validate products and technology Collaborate with Safety teams to embed safety-by-design principles into all agent platform products, ensuring robust safeguards and monitoring capabilities Define success metrics and KPIs for agent platform adoption, safety, and ecosystem health, establishing data-driven decision-making processes Engage with external developers, enterprises, and researchers to understand user needs and gather feedback on agent platform capabilities Drive competitive analysis and market research to inform product positioning and differentiation strategies Establish product requirements for agent evaluation systems, working with Research teams to define comprehensive capability and safety assessments, and to ensure that future model capabilities align with agent platform priorities Lead go-to-market planning for agent platform features, coordinating with Marketing, Sales, and Developer Relations teams Communicate product updates, strategy, and progress to executive leadership, the broader organization, and externally. You may be a good fit if you: Have 7+ years of product management experience, with a strong track record of shipping complex technical products at scale Have deep experience with AI/ML products, developer platforms, or infrastructure products which other teams build upon Possess strong technical intuition and can engage meaningfully with both Research and Engineering teams on architecture, performance, and implementation details Are passionate about AI safety and understand the unique challenges of building reliable, interpretable agentic systems Can translating between research breakthroughs and market opportunities, bridging the gap between cutting-edge capabilities and user needs Are skilled at driving consensus across diverse stakeholders with different priorities, timelines, and success metrics Have a proven ability to define product vision and strategy for emerging technology categories where best practices are still being established Demonstrate excellent analytical and strategic thinking skills, with experience using data to inform product decisions Possess outstanding communication skills and can articulate complex technical concepts to both technical and non-technical audiences Thrive in fast-paced, ambiguous environments where you need to balance multiple competing priorities and constraints Strong candidates may also have: Experience building developer-facing products, platform APIs, or infrastructure that enables third-party innovation and third-party ecosystems Knowledge of agent architectures, tool-calling systems, or multi-modal AI applications Experience with evaluation methodologies for AI systems, including capability assessments and safety evaluations Experience delivering innovative infrastructure to enterprise customers in industries like financial services, life sciences, and the public sector, especially AI systems. Track record of successful go-to-market execution for technical products in competitive markets Experience with open-source ecosystems, developer communities, and ecosystem development Familiarity with AI governance, compliance, and regulatory considerations for AI systems Background in protocol design, standards development, or technical specification processes Representative projects: Defining the long-term product vision for how AI agents should interact with external systems, balancing capability, safety, and user experience, including authentication, authorization, and information security / privacy recommendations Guiding the product strategy for Model Context Protocol (MCP) evolution, including feature roadmap, ecosystem development, and adoption metrics Driving the development of comprehensive agent evaluation products that serve both internal research needs and external developer requirements Establishing product requirements for agent safety systems, including real-time monitoring, intervention capabilities, and audit trails Coordinating the launch of agent platform developer tools, including SDKs, documentation, and support systems across multiple product surfaces Defining success metrics and measurement frameworks for agent platform adoption, ecosystem health, and safety outcomes Leading cross-functional initiatives to integrate agent capabilities into Claude products while maintaining user trust and safety standards Developing partnerships and integrations that expand the agent platform ecosystem while maintaining quality and safety standards The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation. Annual Salary: $305,000—$385,000 USD Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. 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. How we're different 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. Come work with us! 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

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Responsibilities

Own the end-to-end product strategy for Anthropic's agent platform, ensuring alignment across various teams. Collaborate with Engineering and Safety teams to embed safety principles and define success metrics for product adoption.