Note: The job is a remote job and is open to candidates in USA. Level AI is building the LLM-native platform for customer experience. The Revenue Operations Architect will design and implement systems for sales operations, focusing on building infrastructure and processes that enhance forecasting, deal management, and go-to-market strategies.
Responsibilities
- A simplified, high-accuracy forecast off two sources only — Gong + Salesforce — on a MEDDICC-based commit/best-case structure with a +/-5% accuracy target and a weekly CRO cadence
- The deal desk: pricing guardrails, discount authority, and quote governance — built to move fast without leaking margin
- Territory and quota models: capacity planning, attainment tracking, and clean routing logic owned in Salesforce
- The signal layer: product usage and intent data routed into a scored queue for BDRs and AEs
- GTM AI agents you architect and ship — research, sequencing, forecasting, and daily pipeline briefings — productionized, not prototyped
- An ICP scoring model that sharpens itself as deal data compounds
- A live executive dashboard: pipeline coverage, conversion, ramp velocity, NRR, and forecast accuracy — self-serve, not a weekly manual pull
- The systems and data hygiene that make every number above trustworthy
- Own cross-functional GTM projects end to end (pricing changes, launches, new-segment entry) with named owners and a clear definition of done on every line
- Partner with Marketing to keep one pipeline definition and one source of truth — no parallel systems, no competing data
Skills
- 6+ years in RevOps, GTM engineering, or sales strategy at high-growth B2B SaaS/AI — ideally through the $20M–$100M ARR scaling phase
- Hands-on builder. You've personally built forecasts, routing logic, deal-desk rules, dashboards, or GTM automations — not just directed a team that did
- Deep, working fluency in Salesforce and Gong; strong analytical and systems-design instincts
- A bias toward shipping and finishing: you scope tightly, deliver, and close the loop rather than leaving projects at 80%
- Comfort building with AI tooling (Claude, agents, LLM-driven workflows) as a core part of the stack, not a novelty
- Able to influence a tenured, change-resistant seller base by proving value first, then driving adoption
- CPQ / Salesforce architecture depth
- Experience with outbound data infrastructure (enrichment, sequencing, intent)
- Enterprise sales motion and complex-deal support
Company Overview