AI Outcomes Manager, Ema
$135-220k
Salary applicable to California applicants
Universal AI employee
Be an early applicant
Universal AI employee
21-100 employees
Be an early applicant
$135-220k
Salary applicable to California applicants
21-100 employees
Company mission
To build the next-generation AI technology to empower every employee in the enterprise to be their most creative and productive.
Role
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
What the job involves
- 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
- 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
- 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
- Change Management & Adoption:
- Design and execute change-management and rollout plans with customer leadership
- Drive adoption across teams, roles, and geographies
- Stakeholder Management & Escalation:
- Serve as the first escalation point during implementation, go-live, and hypercare
- Manage communication across business, IT, security, and executive stakeholders
- Expansion & Strategic Growth:
- Identify opportunities for additional SOWs and new use cases
- Consultatively sell outcomes using Challenger-style methodologies
- Product & Roadmap Partnership:
- Act as the voice of the customer to Product and Engineering
- Translate VOC, usage data, and failure patterns into actionable insights
Our take
Ema is looking to empower enterprises with universal AI employees. Essentially, these are AI agents built to support the work of other employees by taking on the most repetitive tasks - leaving real people to be more creative and productive.
As the use of automation explodes, businesses need ways to be more efficient and innovative in order to remain competitive. Ema supports this on both ends by taking away the work that can bog down employees and speeding up this work in the process.
Having raised substantial funds, the company is looking to further develop its proprietary tech that powers the AI employees. Ultimately, the agents will be configurable by enterprises so clients can fine-tune them to their needs, and employ them in any role in their organisation.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Jul 2024
$36m
SERIES A
Mar 2024
$25m
SEED
Total funding: $61m
Company HQ
SoMa, San Francisco, CA
Leadership
Surojit Chatterjee
(Co-Founder & CEO)Member of the Board of Directors at Meesho. Former Executive in Residence at Andreessen Horowitz, CPO at Coinbase, Board Member at Olive and VP at Google.
Souvik Sen
(Co-Founder & CTO)Was VP of Engineering at Okta and Engineering Lead (Data and ML, Privacy and Safety) at Google. They also worked as a Principal Research Scientist at Hewlett-Packard Laboratories.
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