Head of AI · AI & Data Science · Gurgaon · India
Head of AI AI & Data Science Recruitment
Gurgaon
60+ AI & Data Leadership Placements — typical mandates close in 105-130 days, with a 12-month candidate guarantee.
Specialisation withinTechnology & Digital·AI & Data Science·Gurgaon, Haryana (NCR)
A Head of AI mandate at a Gurgaon-anchored AI-and-data-science platform is a corporate-HQ-and-enterprise-customer-anchored Gen-AI-and-LLM platform stewardship, multi-year enterprise-Gen-AI architecture compounding and NCR-AI-engineering-talent-acquisition-and-retention discipline seat before it is a P&L seat. The successful candidate owns the multi-year enterprise-Gen-AI-and-LLM architecture across MNC-corporate-HQ-anchored enterprise-AI, financial-services-Gen-AI, telecom-Gen-AI and consumer-internet-Gen-AI customer cohorts, governs the venture-and-strategic-capital sponsor-board governance architecture, holds the NCR-AI-engineering-talent-acquisition-and-retention discipline, and reads the multi-stakeholder operating cadence CEO, CTO, sponsor-board and corporate-HQ-customer-advisory-board together require.
The Head of AI Seat in AI & Data Science, Gurgaon
Head of AI mandates at Gurgaon AI-platforms are structurally the cost-efficient leadership-recruitment tier. The Gurgaon NCR-corporate-HQ-and-enterprise-Gen-AI cluster, the venture-and-strategic-capital-backed AI-platform cohort and the proximity to MNC hyperscaler-and-enterprise-AI Country Head offices shape the bench architecture.
We over-index on operators who have led a Tier-1 corporate-HQ-and-enterprise-customer-anchored AI-platform through a sustained multi-year Gen-AI-and-LLM architecture compounding cycle, navigated an enterprise-Gen-AI deployment cycle as the accountable Head of AI, or held credible CEO, CTO and venture-and-strategic-capital sponsor-board dialogue alongside Head of AI governance.
Why Gurgaon for AI & Data Science Leadership
Gurgaon-NCR anchors India's corporate-HQ-and-enterprise-customer-anchored Gen-AI-and-LLM platform cluster — the corporate-HQ-anchored AI-and-Gen-AI platforms, the MNC-corporate-HQ enterprise-Gen-AI customer base, the listed-parent enterprise-Gen-AI-platform cohort and the broader NCR AI-and-Gen-AI cluster operate from the city. The NCR proximity to MNC hyperscaler Country Head offices and the NCR AI-engineering talent ecosystem shape the bench architecture.
Head of AI / Gen AI / LLM Profile — AI & Data Science in Gurgaon
Gurgaon Head of AI candidates typically come from one of three benches: prior Head of AI / Head of Gen AI / Head of Enterprise AI tenure at a Tier-1 venture-or-PE-backed corporate-HQ-and-enterprise-customer-anchored AI-platform, prior senior AI-leadership tenure at a global enterprise-AI-or-hyperscaler-AI platform with subsequent India-Head of AI crossover, or prior India-Principal-AI-Researcher-or-Enterprise-AI-Solutions-Lead tenure at a Tier-1 AI-platform with subsequent Head of AI crossover. The seat requires multi-year enterprise-Gen-AI-and-LLM architecture credibility, corporate-HQ-customer-stewardship discipline, NCR-AI-engineering-talent-acquisition-and-retention architecture and the venture-and-strategic-capital-board governance rhythm.
Compensation Benchmark
Tier-1 Gurgaon corporate-HQ-and-enterprise-customer-anchored Head of AI packages typically land ₹2-6 crore fixed cash for venture-or-PE-backed-platform Heads of AI, 40-80% short-term incentive tied to enterprise-Gen-AI-customer-acquisition and AI-talent-retention KPIs, plus material ESOP / RSU vesting tied to venture-and-strategic-capital fundraising. Foreign-OEM India Head of AI / Head of Enterprise AI equivalents with Gurgaon-anchor command ₹5-14 crore fixed (frequently dollar-denominated with RSU vesting on global parent stock).
Key Leadership Challenges in AI & Data Science
Inherited from the AI & Data Science parent practice. Each challenge calibrates differently for a Head of AI mandate in Gurgaon.
Hiring a Chief AI Officer or Head of AI who can bridge research credibility, applied product delivery, and board-level AI governance — a combination that is rare in any single candidate.
Building an AI platform team — training infra, serving infrastructure, feature stores, MLOps, evaluation frameworks — that can support multiple product lines without becoming a bottleneck.
Responsible AI leadership — Heads of Model Risk, AI Governance, and AI Ethics who can operate under DPDP, GDPR, and emerging EU AI Act frameworks while not blocking commercial velocity.
Chief Data Officer hires — CDOs who can unify data contracts, governance, and a single logical data plane while enabling self-serve analytics and AI-ready data products.
Senior individual contributor hiring — principal research scientists, distinguished AI engineers, and applied research leads where a single hire can shift technical trajectory.
GCC AI leadership — site leads for global AI platform teams who can operate as dual-reporting leaders to global AI heads and Indian country MDs.
Candidate Archetypes for Head of AI AI & Data Science
The Chief AI Officer
Leader who combines research credibility (typically a PhD from a top-tier institution and published work or production LLM deployments) with applied delivery experience. Fluent in board-level AI governance and commercially bilingual with product and engineering organisations.
The Applied AI VP
Operator who has shipped production fine-tuned, RAG-based, or agentic AI systems at scale. Deep understanding of evaluation, guardrails, prompt engineering at system level, and the MLOps architecture that makes applied AI reliable.
The ML Platform Leader
Infrastructure engineer who has built training and serving infra for foundation-model or high-volume applied-AI workloads. Fluent in GPU scheduling, distributed training, inference optimisation, and the feature-store / model-registry stack.
The Chief Data Officer
Data leader who has rebuilt an enterprise data platform for AI-ready consumption — data contracts, governance, single logical data plane, and self-serve analytics. Often has operated inside BFSI, consumer, or healthcare contexts where data governance is a board-reported topic.
The Principal Research Scientist
Individual contributor with published work in top-tier venues (NeurIPS, ICML, ICLR) or demonstrable contributions to widely-used open-source foundation models. Often a PhD from a top-tier ML research group, with subsequent production experience at a foundation-model lab.
The AI Governance Leader
Risk, compliance, or legal leader who has built a model-risk or AI-governance function. Operates under DPDP, GDPR, and EU AI Act frameworks; understands the intersection of model validation, disclosure, and board-committee governance.
Frequently Asked — Head of AI AI & Data Science Mandates in Gurgaon
Which recruitment firm should I partner with to hire a Head of AI for my Gurgaon enterprise-AI platform?
Leadership-recruitment firms running 12-15% retainer architecture with research-driven slate-building cover the Gurgaon Head of AI bench. Tier-1 Indian executive-search firms typically don't have the AI-research bench depth to pursue these mandates competitively. We run a research-driven slate-building approach with a 60-100 day calibration-to-offer cycle.
How long does a retained Head of AI search for a Gurgaon enterprise-AI platform typically run?
60-100 days from calibration memo to signed offer. Pre-IPO and pre-exit platforms add 2-3 weeks at the back end for venture-and-strategic-capital board and corporate-HQ-customer-advisory-board reference work.
What multi-year enterprise-Gen-AI-and-LLM architecture and corporate-HQ-customer exposure should a Gurgaon Head of AI slate carry?
Direct ownership of a Tier-1 corporate-HQ-and-enterprise-customer-anchored AI-platform multi-year Gen-AI-and-LLM architecture compounding cycle, paired with corporate-HQ-customer-stewardship discipline credibility, NCR-AI-engineering-talent-acquisition-and-retention architecture and venture-and-strategic-capital sponsor-board governance fluency. Operators without enterprise-Gen-AI architecture and corporate-HQ-customer relationship scar tissue rarely clear the second calibration round.
Are returning-NRI candidates viable for Gurgaon Head of AI mandates?
Materially viable for operators with prior global-AI-platform or global-enterprise-AI India-leadership tenure or peer-international enterprise-AI Head of AI experience. The Mumbai–Delhi-NCR capital-markets corridor onboards returning-NRI Head of AI through global-AI-platform and corporate-HQ-and-enterprise-customer-anchored comparators with relative ease.
Adjacent Roles We Place in AI & Data Science
Regulatory & Compensation Context — AI & Data Science
Regulatory Backdrop
AI leadership is hired into an intensifying regulatory envelope. India's DPDP Act has introduced data fiduciary obligations, consent architecture, and cross-border transfer restrictions that shape both ML training data practices and inference pipelines. The RBI's Model Risk Management Guidelines (MRMG) require model inventory, independent validation, and ongoing performance monitoring for any AI used in credit, fraud, or consumer-facing financial decisions. SEBI and IRDAI have both issued consultation papers on AI/ML in capital markets and insurance — not yet fully binding but shaping governance expectations. Globally, the EU AI Act's risk-tier classification, GDPR's Article 22 on automated decision-making, and US state-level AI regulation (New York City Local Law 144, Colorado's AI Act) materially affect leadership candidates hired into India-based roles that serve global products. Responsible AI committees, model-risk registries, and independent AI audits are now standing board-committee topics at leading enterprises. Candidates for senior AI roles are increasingly evaluated on their ability to operate under these frameworks, not just their technical depth.
Compensation Architecture
AI leadership compensation sits at the top end of the technology market. A Chief AI Officer at a well-capitalised AI-first SaaS franchise or a large enterprise commands ₹6-15 crore fixed cash with 1-3% equity and meaningful bonus opportunity tied to technical and product milestones. VPs of Applied AI and ML Engineering price at ₹4-8 crore fixed with 0.5-1.5% equity. Principal research scientists and distinguished engineers — the IC roles — have the most stretched compensation market: US-benchmarked USD cash packages of $400K-$800K plus equity, dual-jurisdiction structures, and signing bonuses that can match fixed cash. CDOs price at ₹3-6 crore fixed. AI Governance and Model Risk leaders, particularly in BFSI, sit at ₹3-5 crore fixed with strong cash bonuses. For GCC AI site leads, comp tracks the global parent's AI leadership band (typically USD-anchored) rather than Indian country-MD bands. Retention is a first-class problem — counteroffers from foundation-model labs and global hyperscalers are now standard on every senior AI exit; we advise clients on retention architecture (refreshers, secondaries, confidential scope expansions) alongside the initial hire.
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