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 experiment — they replace brittle, manual operations with reliable AI systems that deliver measurable outcomes.
Founded by leaders from Google, Coinbase, and Okta, and backed by Accel, Section 32, Prosus, Wipro Ventures, and Hitachi Ventures, Ema operates at the frontier of enterprise AI execution. With teams across Silicon Valley and Bangalore, we are defining how agentic AI is delivered responsibly, reliably, and at scale.
The Director, Customer Delivery & Outcomes owns a portfolio of strategic enterprise accounts end-to-end: every engagement, every outcome, every relationship, every expansion opportunity. Think of this as the McKinsey Associate Partner model applied to enterprise AI delivery.
You are the single point of accountability for your accounts. The customer calls you — not your manager — when they have a problem. You staff delivery teams, oversee solution quality, run executive readouts, measure ROI, drive adoption, rebuild trust when things break, and grow the book through proven production value.
This is not a project management role. This is an account ownership role that combines delivery orchestration, outcome ownership, customer leadership, and commercial growth.
1. Account Ownership
Own your accounts end-to-end: every engagement, every outcome, every relationship. Everything good or bad stops with you.
Be the single point of contact the customer calls for any problem — delivery, quality, adoption, escalation, or expansion.
Maintain a holistic view of each account: engagement status, risk exposure, opportunity pipeline, and the customer’s strategic priorities for the quarter.
Run account planning: engagement roadmaps, resource forecasting, risk assessment, and growth strategy.
2. Delivery Orchestration
Staff and direct delivery teams (Engineering Leads, Implementation Managers, AI Application Engineers) across your accounts.
Oversee delivery quality across all engagements: review solution architectures, attend go-live rehearsals, ensure evaluation rigor.
Manage cross-engagement dependencies within an account (e.g., shared integration infrastructure between parallel deployments).
Serve as the delivery escalation point: join war rooms, coordinate fixes across Engineering and Product, and communicate resolution to the customer.
You don’t write code — but you review architectures, challenge unrealistic scope, and ensure go-live readiness. Your leverage is orchestration and judgment.
3. Outcome Ownership & Continuous Improvement
Own post-go-live outcomes: adoption, ROI, accuracy, and user trust. This role absorbs the Outcomes Manager function for your accounts.
Run regular usage readouts: AI deflection rates, false positive/negative trends, HITL escalation patterns, user bypass rates, and trust signals.
Separate product gaps from process, training, or expectation gaps. Not everything that looks broken is an engineering problem.
Drive continuous improvement cycles: readout → diagnose → prioritize → fix → re-measure.
Communicate outcomes in business language: efficiency gains, cost savings, error reduction — not just dashboards, but diagnosis and action plans.
4. Executive Stakeholder Leadership
Run QBRs with VP/C-level stakeholders: present outcomes, risks, improvement plans, and the strategic roadmap.
Navigate internal customer politics: when the VP of IT and VP of Business disagree on priorities, facilitate alignment around shared success metrics.
Communicate bad news credibly: present the data, the diagnosis, and the recovery plan — without losing trust.
Handle C-level escalations. When the CTO threatens to terminate or the CFO questions ROI, you are the person in the room.
5. Commercial Growth
Grow your book through outcome-driven expansion: deliver the first SOW excellently, measure ROI rigorously, present evidence to the C-suite, then propose the next SOW grounded in proven value.
Identify new use cases by deeply understanding customer business processes and pain points — not by pushing a product catalog.
Know when to push for expansion vs. when to stabilize. Premature expansion erodes trust. You earn the right to grow by delivering first.
Co-sell with Sales: provide the delivery credibility and outcome evidence that makes expansion proposals close.
6. Product & Platform Partnership
Act as the voice of your customers to Product and Core Engineering. Translate field patterns into structured, actionable feedback — not one-off requests.
Identify cross-customer patterns that signal platform gaps or opportunities.
Partner with Product on customer-facing roadmap discussions: what’s coming, what’s not, and how to manage expectations.
7. Team Development
Coach Engineering Leads and Implementation Managers on architecture quality, customer communication, delivery discipline, and outcome thinking.
Promote shared standards and best practices across engagements.
Build reusable account-level assets: engagement playbooks, QBR templates, outcome tracking frameworks, and expansion qualification criteria.
Required
15+ years in enterprise technology delivery, consulting, account management, or customer leadership.
5+ years owning enterprise accounts end-to-end: delivery, outcomes, relationship, and growth — not individual projects within someone else’s account.
Track record managing or directing delivery teams (Engineering Leads, TPMs, consultants) assigned to their accounts.
Post-go-live outcome ownership: measured ROI, tracked adoption, driven continuous improvement, and rebuilt trust after production issues.
Commercial accountability: grown account revenue through outcome-driven expansion, not just retention.
Enterprise stakeholder management at VP/C-level across multiple concurrent accounts.
Production track record — beyond POCs. Scale and accountability required.
Preferred
Experience with AI, automation, or agentic workflow platforms in production.
Background at a consulting firm (McKinsey, BCG, Deloitte) or enterprise SaaS PS org (ServiceNow, Salesforce, UiPath) in a delivery-heavy account leadership role.
Experience with partner-mediated delivery (delivering through consulting partners to end clients).
Familiarity with enterprise integrations (APIs, auth, CRM/HRIS/ITSM platforms) at a judgment level, not implementation level.
Experience in a scaling startup ($5M–$50M ARR) where account management practices were being built, not inherited.
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