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 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 building and shipping real AI systems that work in production , this role is for you.

Who You Are

The AI Implementation Manager owns the delivery and stabilization of Ema’s agentic AI solutions — from commitment through production rollout and steady state. This is not a research role, a support role or a coordination only project management role. You are the delivery leader and technical anchor during implementation, working closely with Value Engineering, Product, Engineering, Infrastructure, and customer IT and business teams. You build rare expertise in production-grade AI delivery. You help set the bar for how agentic AI is delivered in production and prove that AI systems can be implemented responsibly, not heroically. You help enterprises move from manual processes to reliable AI execution.

What You’ll Work On

1. End-to-End AI Delivery Ownership

• Own delivery from design alignment through production rollout and stabilization
• Ensure solutions align with Ema’s agentic architecture and platform capabilities

2. Feasibility Judgment & Agentic Workflow Translation

• Develop a deep understanding of the customer’s business processes and constraints
• Translate business workflows into feasible agentic AI workflows

3. Technical Oversight & De-Risking

• Provide delivery-focused technical oversight without being the primary builder
• Anticipate where AI implementations break — integrations, data quality, scale, edge cases

4. Stakeholder Leadership (Internal & External)

• Act as the primary delivery point of contact for customer business and IT stakeholders
• Coordinate across Engineering, Product, Data, Infrastructure, and Value Engineering

5. Delivery Management Under Pressure

• Coach stakeholders and teams during high-stress phases
• Reduce chaos — not amplify it — when things go wrong

6. Progress, Reporting & Stabilization

• Communicate delivery progress, risks, and decisions clearly to all audiences
• Track success through adoption signals and outcome-adjacent metrics , not just features

7. Team Leadership & Enablement

• Provide day-to-day delivery leadership and mentorship
• Promote shared standards, clear ownership, and delivery discipline

Who You Are

• You have 8+ years in technical delivery, implementation management, or program leadership roles
• You have experience with agentic AI, automation, or workflow orchestration platforms
• You have proven experience delivering