Senior Director of Business Operations

Instrument the full customer journey, from pre-funnel and partner activity through credit consumption and expansion. At our scale, this is a weeks-not-months deliverable.

Define the GTM data model, funnel stages, and metric definitions so numbers reconcile across Sales, CS, Partnerships, and Finance.

Connect product usage and billing data to the revenue stack so every customer is represented completely and consistently.

Govern CRM fields and data quality through automation and clear standards, not manual cleanup.

Design and run a forecasting rhythm built for a consumption-based, land-and-expand model: channel and marketing activity into pipeline, new-logo velocity, consumption trajectories, and expansion revenue.

Present completed-quarter results and forward guidance to the ELT at each quarter-end.

Give ELT members the analysis, forecasts, and materials they need to run their functions and report upward.

Run forecast reviews, pipeline inspections, and business reviews as forums for decisions, not status updates.

Use the data to pressure-test plans and flag risk early, even when the conclusion is unwelcome.

Build AI-driven reporting and analysis across solution presentation, adoption, credit consumption, and customer outcomes, with Backstory as the primary source of truth.

Deliver automated briefings, pipeline intelligence, and self-serve analytics to the whole GTM organization, not just leadership.

Make build, buy, or connect decisions for the GTM data and tooling that power instrumentation and the intelligence layer.

Re-anchor our early warning system around solution adoption: credit consumption, feature activation, workflow integration depth, CS engagement, and conversation signals.

Turn those signals into a review cadence and save and expand plays triggered by what customers are actually doing.

Feed adoption-based churn and expansion signals into the forecast, so save and expand plays show up in projected revenue.

Comp plan design for Sales, CS, and Partnerships, in partnership with Finance and People.

Territory, quota, and capacity planning, including clear rules of engagement and handoffs across direct, CS, and partner teams.

CPQ and pricing approvals, from quote to close.

Lead routing across marketing, sales, CS, and partners, with defined service levels.

Day-to-day CRM administration and the health of revenue-critical systems.

Run Backstory's GTM on Backstory, learning from our strongest adopters and trying uses customers that have not yet tried.

Document the results so they can be referenced in customer and prospect conversations.

Engage with customers and the market as a practitioner of the platform.

Applied AI. Deep understanding of the AI tooling landscape and the ability to make informed tooling decisions and understand where Backstory fits. You have deployed LLMs and AI tools in operational workflows, not just evaluated them. You know where AI outperforms traditional automation and where it adds risk. You have experience building the right AI infrastructure and supporting the change management required.

GTM operating model fluency. You have run GTM operations through a real business model change, ideally consumption-based, land-and-expand, or channel-augmented. You can set the right metrics framework and put it in place without a long assessment phase.

Data architecture literacy. You understand how GTM data is structured and flows across CRM, warehouse, and AI layers well enough to design instrumentation and make build, buy, or connect decisions. You don't need to be an engineer, but you don't depend on one to understand the data model.

Forecasting authority. You know ARR forecasting deeply: where each input comes from, how it is calculated, and where it may be wrong. You can reconcile sources and tell executives how confident to be and why.

Commercial operations depth. You have hands-on experience with comp design, territory and quota planning, CPQ and pricing approvals, lead routing, and CRM administration.

SaaS metrics fluency. You can connect ARR, GRR, NDR, CAC, pipeline coverage, capacity, and productivity to how the business actually performs.

Modern data tooling: working knowledge of SQL, dbt, or BI tools.

Executive presence. You can present a difficult conclusion to the ELT without hiding behind the analysis, and push back constructively when the data calls for it.

Experience. Typically 10+ years in revenue operations, GTM operations, or GTM strategy at a growth-stage B2B SaaS company, including leading a team.

Chief of Staff or CEO-adjacent experience: translating strategic intent into operating plans, preparing board materials, and managing cross-functional work without formal authority.

Channel and partnership operations: tracking, attribution, and handoffs between partner-sourced and direct pipeline.

Usage- or consumption-based pricing: structuring and governing credit-based deals.