AI Outcome Manager
$135k - $220k USD
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.