What You’ll Do

1. Outcome Ownership & Value Realization

• Own customer success from post-sales handoff through post-go-live
• Define and align success metrics, ROI targets, and usage KPIs
• Track efficiency gains, accuracy improvements, cost savings, and experience impact
• Communicate outcomes through QBRs, exec readouts, and customer newsletters

2. Usage Intelligence, Readouts & Continuous Improvement

• Own regular customer readouts of AI usage patterns, adoption trends, and workflow performance
• Analyze false positives, false negatives, failures, and negative feedback across agent behavior, integrations, and UX
• Separate system gaps vs. process, training, or expectation issues
• Partner with Value Engineering and AI Implementation teams to drive prioritized improvements across agents, orchestration, prompts, UX, and integrations

3. Change Management & Adoption

• Design and execute change-management and rollout plans with customer leadership
• Drive adoption across teams, roles, and geographies

4. Stakeholder Management & Escalation

• Serve as the first escalation point during implementation, go-live, and hypercare
• Manage communication across business, IT, security, and executive stakeholders

5. Expansion & Strategic Growth

• Identify opportunities for additional SOWs and new use cases
• Consultatively sell outcomes using Challenger-style methodologies

6. Product & Roadmap Partnership

• Act as the voice of the customer to Product and Engineering
• Translate VOC, usage data, and failure patterns into actionable insights

Who You Are

• You have 12+ years in enterprise customer success, transformation, or solution leadership roles
• You have proven experience delivering measurable ROI post-implementation
• You have track record managing large, complex enterprise accounts
• You have experience working cross-functionally with Product and Engineering teams
• You have background beyond POCs — production, scale, and accountability are required
• You have experience with AI, automation, or digital transformation programs
• You have exposure to regulated or complex enterprise environments
• You have experience in fast-growing startups or scaling enterprise AI platforms
• You have familiarity with outcome-based selling or consulting methodologies
• You have strong understanding of enterprise workflows and process automation
• You have the ability to reason about AI behavior in production, including failure modes and edge cases
• You have the comfort discussing agentic systems, integrations, and UX tradeoffs with credibility

For California based candidates:

The standard base salary for this position is $135,000-$220,000 annually.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.