Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Communication @ 3
API @ 3
Claude Code @ 3
AI @ 3
Change Management @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The company builds AI systems intended to be safe and beneficial, with a multidisciplinary team of researchers, engineers, policy experts, and business leaders.
About the role
Join Anthropic's Customer Success team in a high-visibility, high-impact role driving AI adoption across strategic Digital Native Business (DNB) accounts. As the dedicated Enterprise Customer Success Manager for a global technology leader (100k employees), you will act as a strategic partner and trusted advisor across Anthropic’s Claude capabilities — API, Claude for Enterprise, and Claude Code.
You will develop deep partnerships with customer stakeholders to understand business objectives, strategic direction, AI vision, and technical needs. Partnering with the broader account team, you will help customers select the right Claude capabilities, provide best practices and guidance, and support growth in usage (consumption and seat-based).
Your focus will include scaling customer usage, driving model and use-case optimizations, implementing change-management strategies, and expanding use cases across the organization. Insights from customers will inform Anthropic’s research priorities, product development, and go-to-market strategies.
Responsibilities
- Build trusting, strategic relationships with decision makers in complex, matrixed organizations; understand business objectives and identify optimization and expansion opportunities
- Become an expert in Anthropic products across API, Claude Code, and Claude for Enterprise; understand technical nuances and best practices to guide customers
- Proactively drive usage planning and understand current and future consumption/adoption across consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products
- Monitor usage patterns, identify optimization opportunities, and address underutilization to drive value from contracted commitments
- Serve as the customer’s thought partner: socialize product roadmaps, drive awareness of new products, and engage Product PMs
- Document and quantify customer value (business outcomes, ROI, impact metrics) to build internal business cases for expanded investment
- Identify new use cases and lines of business, partnering with customers, Sales, and Product to discover applications across departments and workflows
- Develop and execute change management strategies to drive end-user adoption, including Train the Trainer programs and Center of Excellence development
- Own the customer experience across the lifecycle: manage account and success plans, conduct Quarterly Business Reviews, and act as the primary conduit between the customer and Anthropic
- Create scalable engagement strategies and playbooks for use across other high-touch strategic DNB accounts
Requirements
- 8+ years of experience in Customer Success, Technical Account Management, or Solutions Engineering
- Experience working with F100 and F500 technology companies, SaaS platforms, or digital-first businesses (high-growth and established tech companies preferred)
- Deep understanding of the AI landscape, including experience with large technology companies and investments/products across the AI tech stack
- Technical fluency to understand and articulate AI/ML concepts, API integrations, and software implementation patterns to diverse stakeholders (developers, product managers, executives, end users)
- Experience driving success across consumption-based and seat-based business models, with understanding of expansion levers and success metrics
- Strategic mindset to identify growth opportunities and translate them into actionable expansion plans
- Proven track record managing a portfolio of accounts while maintaining relationships and driving measurable outcomes
- Strong cross-functional collaboration skills and a customer-centric mindset
- Passion for AI and interest in responsible development of advanced systems
- Ability to manage complexity and a "roll up your sleeves" mentality
Compensation
- Annual Salary: $260,000 - $315,000 USD
Logistics
- Education: Bachelor’s degree in a related field or equivalent experience required
- Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time (some roles may require more time)
- Visa sponsorship: Anthropic states they sponsor visas and retain an immigration lawyer to assist, though sponsorship may not be possible for every role/candidate
Benefits
Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and collaborative office spaces.
How we're different
Anthropic focuses on large-scale, high-impact AI research and values collaboration, communication, and pursuing steerable, trustworthy AI. The team’s research background includes directions related to GPT-3, interpretability, scaling laws, learning from human preferences, and other high-impact AI topics.