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 capabilitie
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 complex, customer-facing enterprise systems
You have Hands-on exposure to AI or automation systems in production
You have experience working across Engineering, Product, and customer IT teams
You have track record beyond pilots — production, scale, and accountability required
You have familiarity with cloud platforms (AWS, GCP, Azure), APIs, and enterprise integrations
You have background in fast-growing startups or enterprise platform companies
You have strong Technical and Delivery Judgement and prior experience stabilizing systems post go-live under real pressure