--- title: 'Sales Operations at Metaprise' canonical: 'https://feeny.ai/job/sales-operations-metaprise-new-york-7vs1zmvjdr2g' type: 'job' last_seen: '2026-09-12' --- # Sales Operations at Metaprise - **Company:** Metaprise - **Location:** New York, NY - **Compensation:** $70k–$100k - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-04-06 - **Last confirmed live:** 2026-09-12 - **Apply:** https://jobs.lever.co/metaprise.ai/d6932bf0-b78e-44e8-ae5d-6bb4eb369d57 ## Job description ## Why This Role Deserves Your Attention Let's skip the pitch. Enterprises are deploying AI agents at scale. The conversations are happening in boardrooms, not on slides. And when the right question lands — how do we actually govern this, integrate this, trust this at scale — someone has to be in the room who can answer it. That's the problem this role exists to solve. Metaprise is building the Agent Operating System for enterprise AI workforces. A unified execution runtime. Built-in identity, authority, and audit. A mission-based model where work gets done — and proven. Deployable across cloud, hybrid, or air-gapped environments. When a prospect asks how that fits into their existing stack — their cloud infrastructure, their orchestration layer, their compliance framework — we need someone who can show them, not just tell them. That's you. ## What You'll Own You are the bridge between what we've built and what the customer needs to believe. You'll take complex problems — governance gaps, integration friction, trust deficits in multi-agent systems — and translate them into working demonstrations, technical narratives, and solution architectures that make the path forward clear. Specifically: Anchor every enterprise deal with technical credibility. You're in discovery sessions, architecture reviews, and proof-of-concept scoping from day one — not brought in after the relationship is already formed. Own the demo environment. You build, maintain, and continuously sharpen the scenarios that prove our value in the moments that matter. You know which story lands with a Chief Risk Officer, which one lands with a Head of Engineering, and you adapt in real time. Design and execute POCs that close deals. You scope what's realistic, structure what's compelling, and deliver proof that removes the last objection standing between interest and commitment. Translate field signals back into product. You're not just a presenter — you're the function closest to what enterprise buyers actually need. When you see a recurring gap, a missed angle, or an emerging use case, you bring it back to the team with enough clarity that it becomes a roadmap decision. Work directly with the CEO and GTM lead. There's no solutions layer between you and the conversations that matter. You're a strategic partner in every major deal. ## Who You Are We're not looking for someone who has done this the longest. We're looking for someone who does it best. The baseline: Bachelor's degree or above. Experience in a pre-sales, solutions engineering, or technical sales role. You've run discovery, built demonstrations, architected proof-of-concepts, and delivered technical presentations to enterprise audiences. You know what it means to own the technical side of a deal. What your week actually looks like: You're in a discovery call with a financial institution's Head of AI, understanding where their agent deployment is breaking down and mapping it against our architecture. You're building a POC scenario for a healthcare organization that needs to show their compliance team exactly how audit trails work. You're on a call with a cloud infrastructure partner, working through how Metaprise fits into their reference stack. You're back at the office with the CEO, debriefing what you heard and deciding what it means for how we position next quarter. What makes you right for this: You're comfortable in the room with technical buyers and comfortable on the whiteboard with engineering teams. You don't need those to be separate conversations. You can explain what an agent execution runtime does in terms a CFO understands and in terms a platform architect respects. Both need to walk away convinced. You have strong instincts about where a deal is technically stuck versus commercially stuck — and you know which one is your problem to solve. You build demonstrations that do the work a slide deck can't. Not polish for its own sake — clarity that removes doubt. You treat POCs as commitments, not experiments. You scope what's winnable, deliver what you promised, and use the outcome to accelerate the next decision. What This Journey Gives You A real technical seat in a company building foundational AI infrastructure. You're not supporting a sales team. You're a peer of it. Direct access to enterprise conversations at the highest level — C-suite, risk leadership, infrastructure architects at major financial and healthcare institutions. The exposure most people spend a decade accumulating. A career-defining scope. The person in this role will help define how enterprise AI governance gets evaluated, demonstrated, and trusted. That's a story worth building. A path to leadership. As we scale, this role grows with it. Whether that's a VP of Solutions function or a broader GTM leadership seat, the opportunity is built into the architecture of this team. Competitive compensation with meaningful performance upside. When you move deals forward, you share in what that creates. A Note on Fit This role works best for someone who is energized by ambiguity, not frustrated by it. There's no existing demo library to inherit. No pre-built POC playbook. You'll build those things — and that's the opportunity, not the obstacle. If you need heavy process infrastructure and a defined enablement program before you can operate, we're not the right fit right now. If you want to be the person who builds that infrastructure, keep reading. Details Location: New York City. On-site, five days a week. Enterprise relationships at this level are built in person — in client offices, in working sessions, and in the kind of conversations that don't happen over Zoom. Compensation: Competitive base with performance-based upside. Details discussed during the process. Reports to: CEO / Founder How to Reach Us Send a note directly to our founder. Tell us what you've built technically, what you've helped close commercially, and why this specific problem — governing and trusting AI agents at enterprise scale — is one worth working on. We respond within 5 business days. Every time. ## About Metaprise ## Company Overview - **One-liner**: Metaprise is the Enterprise Agent Operating System — a unified platform for deploying, orchestrating, governing, and trusting AI agents at scale, primarily serving regulated enterprises. - **Entity Type**: Private (bootstrapped; no external funding raised) - **Headquarters**: New York, NY, United States - **Founded**: 2021 - **Founders**: Richard Swang and Richard S Wang ## Core Business - **Primary industries**: Enterprise AI infrastructure, Agent orchestration & governance; originally focused on AI-driven accounts receivable/payable automation, now positioned as a horizontal agent OS. - **Target customers**: Regulated enterprises – regional banks, capital markets firms, healthcare systems, insurance carriers (B2B, Enterprise). - **Mission/purpose**: To provide a trusted, governed runtime for AI agents in the most demanding compliance environments, enabling safe and auditable autonomous execution. ## Products & Services - **Metaprise Platform (Enterprise Agent OS)**: Nine integrated modules covering agent marketplace, model access, execution runtime, orchestration, observability, and governance. All modules are production-grade and included at no additional cost. - **AURA (Core Governance Engine)**: Four-layer runtime (OrgKernel, Mission Layer, Runtime, Control Plane) providing durable execution, Saga compensation, heartbeat monitoring, policy enforcement, and multi-region replication. Every agent execution is wrapped in an ExecutionToken and recorded in AuditChain. - **Metaprise LLM**: An open-source LLM (Apache 2.0) based on Llama hybrid architecture, trained on 8+ years of financial, medical, and legal compliance data. All inference is version-locked and auditable. - **Agent Marketplace**: 5,500+ pre-built, verified enterprise agents, 1,200+ MCP servers, 3,200+ ClawHub skills. Agents are risk-rated L1–L4 and deployable in one click. - **Deployment Modes**: Cloud (SaaS, live in 24 hours), Hybrid (control plane managed by Metaprise, data stays in customer VPC), and Enterprise (fully air-gapped, on-premises, live in 4–8 weeks). - **Orchestration & Observability**: 9 built-in agent architectures (ReAct, Tree-of-Thought, Multi-Agent, etc.), full-chain trace viewer, LLM-as-judge evaluation, A/B experiments, and OTel export. All free. ## Market Standing - **Valuation / Market Cap**: Not disclosed - **Key Metric**: 31 employees (25% YoY growth); 8,650 LinkedIn followers (+88.7% yearly); real customers in regulated industries (financial services, healthcare, insurance). - **Notable Investors/Partners**: No external funding raised; partners not publicly listed. - **Growth Signals**: 25% headcount growth in the past year; expanding solutions team; active hiring for multiple roles (AI Engineer, Account Executive, Solutions Architect); platform described as having “real traction” with demanding enterprise customers. ## Competitive Advantages - **AURA Governance Engine**: The only agent runtime built from the ground up for regulated environments – includes deterministic policy engine, authority graph, immutable audit chain, and air-gap support. - **Mission-Based Pricing**: No licenses or seats; customers pay only when a Mission completes successfully, reducing adoption friction. - **Open-Source Core**: OrgKernel (the OS kernel) is Apache 2.0, enabling transparency and customisation. - **5500+ Pre-Built Agents**: Ready-to-deploy agents for common enterprise workflows, each risk-rated and tamper-proof. - **Hybrid & Air-Gap Support**: Sensitive data never leaves customer infrastructure; full on-premises option for the most stringent compliance requirements. ## Strategic Focus - Scaling the solutions and go-to-market function to support growing enterprise demand. - Building a repeatable deployment playbook for Cloud, Hybrid, and air-gapped environments. - Deepening capabilities in financial services, healthcare, and insurance verticals. - Expanding the agent marketplace and partner ecosystem (MCP servers, ClawHub skills). ## Why Work Here - **Impact**: Work on a platform that runs mission-critical AI workloads for the most regulated enterprises – solving hard problems in governance, auditability, and safe agent execution. - **Traction**: Real customers, real revenue, and a product that is production-ready and trusted. - **Team**: Small (31 people) but growing fast – opportunity to shape the culture and processes from an early stage. - **Location & Policy**: On-site in New York City (Midtown); the role requires in-person collaboration with customers and product teams. - **Culture**: Emphasis on rigor, deep technical discovery, and building a “playbook” for future team members. Roles span engineering, product, sales, and solutions. ## Sources 1. [metaprise.ai](https://www.metaprise.ai/) 2. [LinkedIn – Metaprise](https://uk.linkedin.com/company/metaprise-commerce-online-bank) 3. [Tracxn – Metaprise 2026 Profile](https://tracxn.com/d/companies/metaprise/__YW2xnNnP_JDKcHxnTz-EaWQmu4Q6jr-WomMfxyjT-W4) 4. [Lever – Solutions Architect Job Posting](https://jobs.lever.co/metaprise.ai/7d4a5a9f-0902-408c-a1f4-9cb7207f59f9) 5. 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