Chief Digital Officer

The Chief Digital & AI Officer will define and implement the AI and digital strategy for the data centre business at Adani. The role calls for a visionary strategic orientation, the ability to drive change, execute for results, and lead cross-functional data and engineering teams.

The ideal candidate is an entrepreneurial, strategic and analytically driven leader with deep expertise in AI, Machine Learning, Generative AI and data architectures — and with genuine knowledge of data centre build and operations. Here technology is the product, not a support function: the mandate is to use AI and digital to improve PUE and WUE, protect uptime, accelerate time-to-energise and deliver a customer experience that hyperscalers judge as best-in-class.

Education & Certification

• Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Information Technology, Engineering or Business Administration.
• Certifications in AI/ML (Deep Learning, MLOps), Digital Transformation or Cloud AI architectures (Azure/AWS/GCP) will be a strong advantage.
• Engineering background (Electrical, Mechanical, Electronics or Computer Science) is preferred given the critical facility environment.
• 18–22 years of experience overall, with 6–8 years in a senior digital, AI or technology leadership role.

Roles and Responsibilities

• AI-Driven Strategy: define and implement a clearly defined, customer-centric AI and digital transformation agenda aligned with the business strategy across design, build and operations.
• Operationalising AI: design, deploy and run AI-enhanced processes — cooling and thermal optimisation, load and capacity forecasting, predictive maintenance on critical power and cooling equipment, anomaly detection — with ownership of business outcomes.
• Reliability and Efficiency: own PUE, WUE and uptime as primary measures; establish a unified DCIM and BMS data foundation and enforce digitised change and method-of-procedure discipline.
• Customer Experience: deliver a customer portal with real-time power, environmental and capacity telemetry, and automated, audit-ready SLA and uptime reporting.
• Cultural Transformation: inculcate a culture that is AI-first, data-led, agile and attuned to algorithmic thinking, without ever compromising uptime discipline.
• Thought Leadership & Governance: provide thought leadership to senior stakeholders on AI as a lever for growth, and establish robust AI governance, data privacy and ethical AI frameworks.
• Technology Advocacy: educate the business on emerging AI trends (GenAI, LLMs, Edge AI), opportunities and competitive threats — including the implications of AI/GPU workloads for high-density and liquid-cooled capacity.
• Modernisation & AI Infrastructure: make build-vs-buy decisions for AI models and data platforms; convert legacy systems into AI-ready applications through integrated, scalable data architectures (data lakes, MLOps pipelines) spanning DCIM, BMS/EPMS, ITSM and ERP data.
• Security & Compliance: set secure, enterprise-grade AI and data boundaries and data sovereignty controls across IT, OT and physical security, maintaining certifications and supporting customer security audits.
• Portfolio & Partner Ecosystem: manage the AI/digital portfolio with shared accountability for value creation and ROI; grow internal capability and manage an ecosystem of AI vendors, DCIM/BMS OEMs, hyperscalers and start-ups.
• Talent Development: build a world-class team of data scientists, ML engineers and software engineers capable of shipping customer-facing product, not only administering vendor platforms.
• Stakeholder Management: influence and align the CEO, CFO, campus heads, sales and customers to ensure timely delivery of AI solutions.

Sector Knowledge

• Hands-on experience with a colocation or hyperscale operator, a hyperscaler's infrastructure organisation, or a major design/build/commissioning firm serving the sector.
• Working knowledge of critical facility engineering: power topology and redundancy (N+1, 2N), UPS and batteries, generators, chilled water and air-cooled systems, and liquid cooling for high-density AI deployments.
• Comfort with PUE, WUE, uptime/tier classification, SLA constructs, MTBF/MTTR and commissioning Levels 1–5.
• Practical exposure to DCIM, BMS/EPMS, NOC operations and ITSM in live 24x7 environments.
• Familiarity with MeitY and data localisation requirements, CERT-In reporting and renewable/open-access power sourcing.