Senior Partner – Transformation — Machine-Learning Infrastructure Stack

The mandate

Boards are asking the firm for help with transformations in which machine-learning infrastructure has become a material capital, operating and risk decision. Current teams possess much of the necessary technical depth, yet demand for board-level counsel is not served at scale. Engagements often begin as architecture or cost assignments after strategic choices have already been made. The Senior Partner – Transformation will build a proposition that enters earlier, frames the enterprise decision and remains accountable through realised change.

The surrounding platform accounts for approximately ₹800 crore in AI product and services revenue and involves about 250 employees and material partners across India, Mumbai and the wider region. Relevant capabilities include cloud and data foundations, model operations, platform engineering, controls, sourcing, finance and organisation change. Their coexistence is valuable, but it does not automatically produce integrated counsel. Clients need one view of ambition, economics, sequencing and execution risk.

The immediate obstacle is an enterprise-trust gap. Senior clients have seen technology programmes overstate benefits, understate adoption and obscure long-term operating cost. Winning their confidence requires independence from any predetermined architecture and a willingness to challenge both vendors and internal enthusiasts. The practice should help boards decide what to build, buy, defer or stop, then connect those decisions to operational evidence.

Why this seat is open

This is a newly authorised advisory seat, not a replacement. Existing leaders retain their accountabilities until the machine-learning infrastructure remit is activated. A planned four-to-six-month search is intended to place the appointee ahead of the next capital and talent cycle while organisation design remains confidential. The onsite Mumbai role reports to the Global Managing Partner and regional partner council.

What you will own

You will shape a focused transformation thesis around problems for which the firm can offer distinctive board counsel and delivery assurance. It may include infrastructure investment cases, operating-model change, cost and capacity resets, platform governance or recovery of distressed programmes. Every offer should specify the decision maker, baseline, value mechanism, evidence and capabilities required; broad claims of end-to-end transformation are not sufficient.

Origination is personal in the early phase. You will use senior relationships to create conversations around real enterprise choices, qualify opportunities and assemble teams before scope hardens. Signature engagements should demonstrate that strategic counsel and technical depth reinforce each other. Commercial structures need to reflect senior attention, delivery risk and value without promising outcomes outside the firm’s control.

Practice building matters as much as sales. You will appoint proposition leaders, connect technical specialists with sector partners and develop principals through consequential client exposure. Engagement assurance must surface fragile benefits, architecture dependencies and adoption constraints early. Reusable diagnostic and governance assets should improve judgement and delivery, not become generic collateral without tested application.

The first 12 months

The opening 90 days should test the demand hypothesis. Review recent pursuits and delivery, interview board sponsors and senior clients, map the strongest internal experts and inspect the economics of adjacent work. Select a narrow portfolio of board problems, identify anchor relationships and agree investment gates with the partner council. Assess who can lead delivery and who needs development or external reinforcement.

Across months four to nine, originate and launch signature engagements, install a common value and assurance method, and build multidisciplinary teams around the chosen propositions. Publish decision-grade insight from genuine client patterns while protecting confidentiality. Early wins must show trusted counsel and measurable movement in a client outcome, not simply high utilisation or access to a prominent logo.

At year end, the practice should have trusted board access, a small body of signature work and a stronger partner bench. Present a forward book that distinguishes committed fees from relationship potential, along with talent and investment plans. Show how methods transfer across engagements without flattening sector or client context.

What the board will measure

The first-year case should finish within 10% of its approved economics, with forecast changes explained in advance. For three successive quarters, the view of contracted work, cash, pipeline, client outcomes and partner capacity must reconcile. The agreed trust indicator should improve quantitatively from a clean baseline under an identified owner.

Major engagement, conduct and delivery issues are expected to close by their governance dates with evidence of lasting repair. Retention among critical professionals should reach at least 90%, and ready-now cover should be identified for 70% of direct reports. Significant client concerns must not remain outside governance, and any severe escalation older than 30 days requires explicit disposition.

The person

You are a Senior Partner, Practice Leader or Operating Partner with 18–22 years of relevant experience. Your background may span AI, enterprise software, data infrastructure, cloud, analytics or applied research, provided it includes senior-client accountability and multidisciplinary leadership. You have owned at least ₹450 crore in P&L, book, budget or client value and led at least 175 people.

You have originated board-sponsored transformation work whose benefits continued after the advisory team left. Evidence should cover a hard portfolio choice, a machine-learning or infrastructure decision, leadership development and the numerical effect on a client or practice. You can challenge a preferred technology answer while sustaining confidence. References will be asked to separate your influence from the wider firm.

Compensation and terms

The anticipated package is ₹2.2–3.0 crore fixed plus performance variable, calibrated to the final machine-learning infrastructure scope and current mix. A client and conflict transition of up to six months can be structured. The appointment provides regular exposure to the group board and relevant risk and people committees.

Confidentiality

The enterprise, client situations and incumbent teams will remain unnamed until a confidential conversation establishes relevance. Scale and operating circumstances have been rounded and combined to eliminate identifying signals.