AI Outcomes Manager

Ema is building the world’s first Universal AI Employee — an agentic AI platform that automates complex, cross-system enterprise workflows end-to-end, with humans in the loop where it matters.

Unlike copilots or narrow automation tools, Ema deploys production-grade multi-agent systems that integrate deeply with enterprise SaaS platforms and execute real business processes at scale. Our customers don’t run experiments — they replace manual operations with AI-driven systems that deliver measurable outcomes.

Founded by leaders from Google, Coinbase, and Okta, and backed by top-tier investors, Ema operates at the frontier of enterprise AI execution, not demos. With teams across Silicon Valley and Bangalore, we are defining how agentic AI is delivered responsibly, reliably, and at scale. If you care about turning AI into real outcomes, this role is for you.

About the Role

The AI Outcomes Manager owns post-sales value realization for Ema’s enterprise customers. This is not a traditional Customer Success role. You will operate across Ema’s value-realization lifecycle, partnering closely with Sales, Value Engineering, AI Implementation, Product, and senior customer stakeholders. You are the first escalation point when delivery is under pressure and the owner of the closed-loop feedback system between customers, delivery teams, and product. AI value gets lost without strong change management and ownership and Production AI systems generate false positives, false negatives, and edge cases. Customers struggle to interpret usage data and system behavior and Stakeholders demand results under timeline, political, and organizational pressure and AI systems must continuously improve, not stagnate post go-live. In this role you are responsible for solving these systematically and calmly.

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.