Customer Success Manager, Public Sector (National Security)

About the role

As a Customer Success Manager on Anthropic's Public Sector team, you will be the post‑sales trusted advisor helping national security customers realize the value of Claude and turn their investment into mission impact. You'll combine your customer‑success expertise with technical fluency to drive adoption of Claude Code, the Claude API, and Claude for Government (C4G) on classified infrastructure delivered through a cleared cloud provider, while maintaining our high standards for safety, security, and discretion.

Key responsibilities

• Partner with the account executive and Applied AI architect to create an account and success plan aligned with mission objectives and technical implementation.
• Serve as the primary post‑sales advisor throughout deployment, enablement, model migration, renewal, and expansion, building trusted relationships across senior stakeholders.
• Support customers building with Claude Code, the Claude API, and Claude for Government on classified infrastructure, managing configuration, capacity planning, and accreditation requirements.
• Create and deliver enablement and executive content, from hands‑on engineering workshops to mission‑value conversations with senior leadership.
• Drive consumption and adoption by onboarding workloads, monitoring compute usage, and documenting mission‑outcome value.

Required profile

• U.S. citizenship with an active TS/SCI security clearance and full‑scope polygraph.
• Prior experience working with U.S. national security agencies at the AI leadership or platform level.
• 5+ years in customer‑facing roles such as Customer Success Manager, Technical Account Manager, or Solutions Architect, with ability to work onsite in the National Capital Region 3‑4 days per week.
• Experience driving success with consumption‑based and seat‑based products, measuring adoption without direct telemetry.

Required skills

• Technical fluency with AI/ML concepts, API integration patterns, and agentic tooling such as Claude Code.
• Familiarity with common LLM frameworks, tools, and evaluation approaches.
• Hands‑on experience building solutions with an LLM API or coding agent.