Chief Financial Officer – Transformation — Machine-Learning Infrastructure Stack

The mandate

An institutionally backed artificial-intelligence products company is commercialising a machine-learning infrastructure stack without consistent performance visibility. Revenue, compute, hardware, cloud commitments, services and development costs are reported through different views, delaying the close and weakening decisions. An urgent finance transformation must establish trustworthy economics before scale increases complexity.

The Chief Financial Officer – Transformation will steward approximately ₹1,000 crore in AI product and services revenue and lead around 425 employees and material partners. Scope includes controllership, planning, commercial finance, working capital, cost economics, systems, procurement interface, investment governance, reporting and talent. The role reports to the Group Chief Executive and the relevant board committee.

The first priority is a clean economic perimeter. Product subscriptions, consumption, reserved capacity, services, support and research activity should map to customer and product cohorts. The CFO will reconcile accounting outcomes with operational drivers, exposing where allocations or capitalisation obscure the real cost to serve.

Close transformation should remove root causes rather than compress manual work into fewer days. Data ownership, account logic, reconciliations, estimates and review need explicit design. Material adjustments should be traceable, repeatable and supported by evidence. Automation is valuable only when the underlying control and definition are stable.

Decision-quality economics must include infrastructure. Compute utilisation, accelerator commitments, cloud pricing, storage, networking, licences and engineering support affect margin. The CFO will distinguish strategic reserved capacity from idle cost and ensure product pricing reflects consumption and service obligations.

Commercialisation adds revenue and working-capital complexity. Contract terms, deployment acceptance, usage, billing, credits and collection should connect. The role will identify customer or process causes of delay and release cash sustainably, avoiding period-end action that simply shifts timing.

Forecasting should start with customers and capacity. Pipeline conversion, deployment milestones, consumption, compute availability, hiring and supplier commitments should translate into revenue, cash and margin. Ranges need explicit triggers. A variance should arrive with causal explanation and management decision.

Investment governance will compare technical and commercial uses of capital. Platform capability, reliability, efficiency and go-to-market each require evidence and stage gates. Finance must challenge optimism without relying on short-term margin alone, recognising option value where it is deliberately funded.

The finance systems roadmap should support the operating model. Product, customer, contract, capacity and cost data need common identifiers and ownership. The CFO will stop technology changes that automate inconsistent logic or create another reconciliation layer.

Finance leadership must combine control, AI economics and transformation execution. The new executive will assess leaders, clarify programme and line accountability and build succession. The finance team should spend less time reconciling and more time shaping decisions.

Why this seat is open

An accelerated transition has created an urgent replacement. Interim ownership protects statutory and liquidity needs, but finance transformation and commercialisation economics require one permanent leader. The board wants appointment within six to eight weeks.

What you will own

• Establish clean product, customer and infrastructure economics.
• Steward finance across approximately ₹1,000 crore in AI product and services revenue.
• Redesign the close around stable data, controls and ownership.
• Connect compute and capacity consumption to product margin.
• Lead approximately 425 employees and material partners.
• Release working capital through customer and process change.
• Build forecasts from commercial and infrastructure drivers.
• Strengthen finance systems, leadership and succession.

The first 12 months

The first 90 days should reconcile the baseline, meet the 30 stakeholders closest to inconsistent visibility and assess leaders. Stabilise severe close, cash or control risks. Agree economic, systems and investment gates with the board.

Months four to nine should simplify close, implement driver-based forecasts and act on working capital. Improve infrastructure costing, rework weak investments, fix data ownership and fill leadership gaps.

By year end, a clean close, decision-quality economics and released working capital should operate to a reliable cadence. Performance must remain within 10% of approval, with three forecasts aligning AI revenue, infrastructure cash, customers and people. Severe control issues require verified closure inside 30 days.

What the board will measure

• Faster close supported by fewer manual adjustments and reconciliations.
• Product margin reflecting complete compute and service economics.
• Working capital released through durable billing and collection change.
• Forecasts aligning customer deployment with capacity and cash.
• Preserve over nine in ten essential finance specialists and ready cover for seven in ten direct roles.
• Systems changes reducing rather than automating inconsistency.

The person

You are a CFO, Deputy CFO or Group Financial Controller with 22–28 years in AI or an adjacent technology enterprise. You have directly owned financial statements, liquidity decisions and investment cases while transforming performance visibility.

Your accountable P&L, book, budget or portfolio has been at least ₹700 crore, and you have led 300 or more people. Evidence should show close, cash and decision outcomes sustained across two reporting periods.

You understand AI infrastructure economics, finance control and system change. You can challenge capacity optimism, make allocation transparent and retain business followership while tightening evidence standards.

Compensation and terms

Fixed compensation is ₹2.2–3.0 crore plus performance variable. This permanent Gurugram role is onsite and expects relocation, with a structured weekly commute potentially available during the opening quarter. Notice up to six months can be managed.

Confidentiality

The company, predecessor, infrastructure contracts and finance evidence remain confidential. Identifying details will be shared after mutual interest under an undertaking; public facts are composite.