Revenue Operations Lead
About the job
- Four to eight or more years of experience in Revenue Operations, Sales Operations, GTM Strategy and Operations, or Deal Desk at a B2B enterprise software company, supporting deals in the $250K–$1M+ range.
- Demonstrated experience building and owning a process, model, or system from inception.
- Hands-on SQL skills, including querying the warehouse, building models, and auditing results, along with strong spreadsheet modeling skills.
- CRM administration or architecture expertise in HubSpot or Salesforce, including data models, custom properties, workflows, permissions, and integrations.
- Partner or channel operations experience, such as deal registration, partner attribution, co-selling, marketplace transactions, or OEM and embedded revenue.
- Experience owning forecasting and compensation, including calling forecasts, designing or materially rebuilding compensation plans, and defending quota models.
- Commercial judgment sufficient to assess and challenge sales forecasts.
- Ability to operate without analyst, business intelligence, or operations-vendor support.
- Own the weekly forecast process and cadence across direct and partner sales motions, and report forecast accuracy against commit.
- Define opportunity stage definitions with entry and exit criteria configured in the CRM.
- Instrument the CUPMEDDPIC qualification methodology as inspectable fields tied to stage progression.
- Maintain pipeline coverage, conversion, velocity, and stage-aging analysis by segment, motion, representative, and vertical.
- Run pipeline hygiene and inspection routines, and identify at-risk and stalled opportunities before forecast calls.
- Build and own the attribution model distinguishing partner-sourced, partner-influenced, and partner-delivered revenue, with definitions approved by Finance.
- Design and administer deal registration, including registration windows, approval logic, and expiration.
- Establish channel-conflict and account-overlap rules, and arbitrate disputes between direct and partner teams.
- Define revenue treatment and reporting for OEM and embedded arrangements, including revenue share and end-customer visibility.
- Report partner-sourced pipeline and bookings alongside direct sales metrics.
- Design territories and account coverage across direct and partner-facing roles.
- Build the capacity and quota model, including ramp assumptions, and support annual and mid-year planning.
- Design and administer variable compensation plans, including accelerators, multipliers, partner-sourced credit, and split credit between Account Executives and Partner Managers on the same opportunity.
- Own commission calculation accuracy and the dispute process in partnership with Finance and People Operations.
- Own the go-to-market technology stack, including CRM (HubSpot), reporting and warehouse layer (Metabase), enrichment, and sales engagement tools; administer integrations and the roadmap.
- Own the CRM data model, including objects, properties, validation rules, required fields, permissions, and workflow automation.
- Establish data governance and hygiene standards for deduplication, account hierarchy, domain matching, and currency normalization.
- Own the pipeline from the CRM into the warehouse so reporting can be generated in a single query rather than through multiple exports.
- Support pricing and packaging across seat-based, consumption, embedded and OEM, on-premise and air-gapped deployments, and multi-year enterprise agreements.
- Own the approval matrix, discount governance, and review of non-standard terms.
- Reduce paper-process cycle time for MSA redlines, DPA, security questionnaires, vendor onboarding, and purchase order issuance, and run the process in parallel with technical evaluation.
- Own the closed-won handoff data contract between Sales, ETS (pre-sales), and CVE (post-sales delivery), ensuring what was sold is what gets scoped.
- Build reporting on win and loss rates by competitor and motion, ramp curves, cycle time with and without a partner, customer acquisition cost by channel, and expansion signals from live deployments.
- Deliver go-to-market inputs for board and investor reporting in partnership with Finance.
- Retire reporting that does not change a decision.
- Experience at an AI-native, agentic, or automation and orchestration company such as UiPath, Workato, Boomi, or Celonis.
- Familiarity with GSI or hyperscaler ecosystem economics, including practice P&Ls, rate cards, utilization, marketplace private offers, and co-sell programs.
- Experience with consumption or hybrid pricing models.
- Domain exposure to BPO, HRIS and payroll technology, financial services, healthcare, or legal.
- Python or dbt in addition to SQL.
About the company
Ema deploys teams of coordinated AI agents, marketed as AI employees, to run multi-step business processes across HR, IT, and finance on top of a company's existing apps. Its EmaFusion model layer can access more than 150 frontier and open-source models, while Ema provides domain knowledge, integrations, and orchestration to connect them into end-to-end workflows. Clients keep their current software stack; AI agents perform tasks across systems and deliver results to complete end-to-end tasks, with pricing based on completed tasks and outcomes rather than seats or tokens. The goal is to automate and optimize business processes at scale for large organizations and to expand globally through expanded sales and markets.
Company Size
201-500
Company Stage
Series B
Total Funding
$152M
Headquarters
Mountain View, California
Founded
2023
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Simplify's Take
What believers are saying
- Ema closed $77 million on September 23, 2026, led by Creaegis.
- TechCrunch reported over 50 active deals, 1 million users, and $150 million bookings.
- Wipro, Hitachi, ADP, PwC, Google, KPMG, and Microsoft validate enterprise demand.
What critics are saying
- Microsoft, UiPath, and Writer already own adjacent enterprise workflows.
- Ema still sells through demos, slowing adoption against self-serve rivals.
- A failed APAC, South America, or Middle East push would trap growth in one region.
What makes Ema unique
- EmaFusion routes tasks across 150 models, reducing single-model dependence.
- Ema prices by completed outcomes, not seats or tokens.
- Ema ships prebuilt HR, IT, and finance agents with 250 connectors.
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Benefits
Hybrid Work Options
Growth & Insights and Company News
6 month growth
↑ 3%1 year growth
↑ 13%2 year growth
↑ 1%Ema, a startup deploying AI agents to automate corporate processes across HR, IT, and finance, has raised $77 million in Series B funding led by Bengaluru-based Creaegis. Existing investors Accel, Section 32, and Prosus also participated. The round brings Ema's total funding to $140 million and more than quadruples its valuation from 2024. Founded in 2023 by former Google and Coinbase executive Surojit Chatterjee and ex-Okta executive Souvik Sen, Ema uses coordinated AI agents to handle multi-step business processes across existing applications. The company has over 50 active enterprise deals and 1 million users, with clients including Google, Microsoft, PwC, and KPMG. Ema's revenue has grown 50-fold over two years, with revenue bookings surpassing $150 million. The startup maintains gross margins near 80% and reports a net dollar retention rate of around 180%. It will use the new capital to expand sales and marketing efforts and enter new markets across Asia-Pacific, South America, and the Middle East.
Ema AI, an enterprise platform for agentic AI employees, has appointed Jonathan Feldman as Head of Revenue, Partnerships and Solutions. The role was created to support the company's expansion of enterprise adoption for its AI employees in HR, IT and finance. Feldman joins from Workato, where he spent four years, most recently as Global Vice President of the AI business unit. At Workato, he built the AI business unit from the ground up and developed strategic partnerships with Anthropic, OpenAI, Google and Nvidia. In his new role, Feldman will lead Ema's revenue, partnerships and solutions organisation, with responsibility for building a scalable partner ecosystem and creating a repeatable enterprise go-to-market motion. Prior to Workato, he held enterprise sales leadership roles at Freshworks, Oracle and SAP. Ema's platform provides enterprise-grade orchestration and pre-built AI employees designed to support business workflows.
Hospital for Special Surgery (HSS) is deploying AI agents for patient scheduling and triage through a collaboration with Ema Unlimited. The 24/7 service uses conversational AI to assess patient conditions via web, text or phone, then books appointments with appropriate clinicians based on location, insurance and availability. The system includes safeguards, with complex cases escalated to human specialists. All AI decisions are auditable and patient data remains secure. HSS filters technology decisions through an AI subcommittee that scrutinises patient-facing applications rigorously. HSS plans to open a dedicated AI lab at its New York campus to democratise access across staff. Dr Barad, who co-chairs the AI subcommittee, emphasises treating agentic AI as general-purpose technology requiring unified data strategy rather than narrow use cases.
Willow Innovations and Ema EQ have launched the Women's Health AI Consortium, the first industry body dedicated to establishing standards and ethical guidelines for AI in women's health. The consortium addresses the historic underinvestment in women's health technology, where AI tools are often built on incomplete data and deployed without sufficient oversight. The initiative is governed by a multidisciplinary board including clinicians, technologists and ethicists. It operates around six core commitments focused on accuracy benchmarks, data transparency and clinical validation. The consortium aims to ensure AI tools reflect women's lived experiences and meet safety standards before widespread deployment. "Women's health AI is moving at a pace that demands immediate, coordinated accountability," says Sarah O'Leary, CEO of Willow. The consortium provides shared standards for organisations developing or deploying AI in women's health.
AI Genesis vs Ema.co: Enterprise AI agents vs SMB Digital Hires. Compare AI Genesis and Ema.co - enterprise AI agents vs purpose-built Digital Hires for SMBs. Pricing, scale, deployment, and which fits businesses with 5-50 employees. Enterprise AI and SMB AI are not the same market. Ema.co raised $61 million in venture capital to build AI agents for enterprise organizations. AI Genesis was founded to build Digital Hires(TM) for businesses with 5 to 50 people. On paper, both companies "do AI." In practice, they serve completely different universes - and choosing the wrong one wastes either your money or your time. This comparison exists because business owners searching for AI workforce solutions keep finding enterprise platforms that weren't built for them. If you run a 15-person operation and you're reading Ema's marketing, you need to understand what you're actually looking at - and what you're not. What each platform actually does. Ema builds what they call "universal AI employees" powered by their proprietary EmaFusion technology - a model orchestration layer that routes tasks across multiple AI models. It's sophisticated engineering designed for Fortune 500 complexity: multi-department workflows, enterprise compliance requirements, massive data lakes, and organizations with hundreds or thousands of employees. AI Genesis builds Digital Hires(TM)- autonomous AI employees purpose-built for specific roles in small-to-midsize businesses. The Genesis Context Engine(TM) ingests your business knowledge. The Genesis Intelligence Layer(TM) makes decisions using that context. The Genesis Automation Core(TM) executes across your actual software stack. Each Digital Hire(TM) is deployed for a defined role - customer service, order processing, appointment scheduling - with the goal of handling that role end-to-end. The fundamental difference: Ema is building horizontal AI infrastructure for enterprises to customize. AI Genesis is delivering a finished, deployed, working employee for your specific business. Head-to-Head comparison. | Feature | AI Genesis | Ema.co | | Target market | SMBs (5-50 employees) | Enterprise (500+ employees) | | Funding model | Bootstrapped, founder-led | $61M+ VC-backed | | Minimum investment | $75K/yr ($5K/mo + $15K setup) | $50K+ minimum (enterprise contracts) | | Deployment | 90-day founder-led deployment | Enterprise sales cycle (3-6 months+) | | Customization | Built around your specific role and data | Platform configured for your org | | Published SMB case studies | Yes - RTR Vehicles ($180K/yr saved) | None for sub-50 employee companies | | Guarantee | Double Down Promise(TM)(2x ROI or free) | None published | | Support model | Direct access to founder and engineering team | Enterprise account management | | Sales process | $2,500 paid assessment | deployment | Multi-stakeholder enterprise procurement | | Architecture | Genesis Context Engine(TM) + Intelligence Layer(TM) + Automation Core(TM) | EmaFusion (multi-model orchestration) | Why Enterprise AI doesn't scale Down. Enterprise AI platforms are built for enterprise problems: data governance across departments, compliance with SOC 2 and HIPAA at scale, integration with SAP and Salesforce Enterprise Edition, approval workflows that involve seven stakeholders, and IT security reviews that take months. None of that applies to a 20-person e-commerce business that needs someone to answer customer questions at 2 AM. When enterprise tools try to serve small businesses, three things happen: * The price doesn't flex. Enterprise sales cycles, implementation teams, and infrastructure costs create a floor. Ema's minimum reportedly starts at $50K - before you've deployed a single agent. For context, many SMBs' entire annual labor budget for the role they want to automate is under $80K. * The timeline explodes. Enterprise deployments take 3 to 6 months of discovery, procurement, security review, and staged rollout. If you're a 15-person business, you need something working in weeks, not quarters. * The product is over-engineered for the problem. EmaFusion's multi-model orchestration is impressive technology. It's also solving for complexity that a small business doesn't have. You don't need model routing across 12 departments when you have 3 departments. What Ema does well. Ema is building serious AI infrastructure. Their EmaFusion technology - routing tasks to the best model for each subtask - is genuinely innovative. For organizations with 500+ employees, complex compliance needs, multi-departmental workflows, and dedicated IT teams to manage implementation, Ema is in the conversation alongside platforms like Sierra AI ($150K-$1.5M/yr) and Ada CX ($50K-$300K/yr). Their $61M in funding means they have the runway to build deeply, hire top talent, and invest in R&D. For enterprise buyers with enterprise budgets, that stability matters. What AI Genesis does differently. AI Genesis was built from the ground up for the businesses that enterprise platforms ignore - the 5 to 50 person operation where every role matters, every dollar matters, and there's no IT department to manage a six-month AI implementation. The deployment model reflects this reality: * $2,500 paid assessment - not a free pilot that goes nowhere, but a focused evaluation that credits toward your setup. You get a concrete analysis of which role to automate, projected savings, and a deployment plan. * 90-day deployment - from assessment to production in one quarter. Not one year. * Founder-led implementation - you work directly with the team building the system, not an account manager relaying messages to engineering. * Double Down Promise(TM)- your Digital Hire(TM) saves at least 2x what you pay, or you don't pay. No enterprise platform offers anything close to this guarantee. The proof is in production. RTR Vehicles - an e-commerce aftermarket auto parts company - deployed a Digital Hire(TM) for customer service. The results: 4 CS representatives reduced to 1 part-timer, 92% of interactions auto-resolved, 8.3-second response times around the clock, and $180K in annual savings. The team members weren't let go - they moved into leadership and operations roles where they create more value. The proprietary technology question. Ema brands their technology stack as EmaFusion. It's smart marketing - a named, proprietary system creates perceived differentiation. AI Genesis has its own purpose-built architecture: * Genesis Context Engine(TM)- ingests and indexes your entire business knowledge base, not generic training data. Your products, policies, customer history, and operational procedures become the exclusive knowledge boundary. * Genesis Intelligence Layer(TM)- the decision-making core that routes queries, applies business logic, and determines when to act autonomously versus when to escalate. Calibrated per-client based on your risk tolerance and operational requirements. * Genesis Automation Core(TM)- the execution layer that operates your real software. Not just API calls - actual software navigation, form completion, order processing, and cross-system workflows. The difference isn't which architecture sounds more impressive. It's which one was built for your business size. Making the right choice. Choose Ema if you have 500+ employees, a dedicated IT team, an enterprise procurement process, multi-departmental AI needs, and a budget starting at $50K+ for a platform that your team will configure and manage. Choose AI Genesis if you have 5-50 employees, specific roles that need coverage, no in-house AI expertise, a need for guaranteed ROI, and a preference for a partner who deploys a working system rather than a platform you configure yourself. Different solutions for different scales. The mistake is trying to force an enterprise tool into a small business, or vice versa. Find out what a Digital Hire(TM) would save you. Run your numbers through the ROI Calculator - it takes 60 seconds and shows you the specific dollar impact for your business. Want the full breakdown of how Digital Hires(TM) work? Download the free playbook - no email sequence, no spam, just the deployment framework. If you're comparing platforms and want an honest conversation about whether AI Genesis is the right fit, book a discovery call. If AI Genesis Inc. is not the right fit, AI Genesis Inc.'ll tell you. Ready to see what a Digital Hire(TM) can do for you? Get the free playbook - the exact framework RTR Vehicles used to save $15K/mo. Then book a strategy call if you want AI Genesis Inc. to map it for your business.