Job Description :

Experience and Qualifications :

- 15- 20 years of experience in AI/ML, data science, or enterprise technology leadership roles including ownership of large-scale AI transformation initiatives

- Demonstrated background in product-led or product-sales environments, with strong fluency in advisory-led, long-cycle enterprise engagement

- Proven experience productionizing AI capabilities in enterprise software or platform environments, with clear evidence of business adoption and measurable impact

- Demonstrated career depth and continuity, with evidence of sustained ownership through full AI product and implementation cycles across organizations and markets

- Strong understanding of applied AI/ML, intelligent automation, document intelligence, and generative AI, with experience in enterprise-scale deployment, governance, and operationalization.

- Familiarity with cloud platforms (AWS, Azure) and API-first architectures

- Experience in BFSI (Banking, Insurance) or other highly regulated, process-intensive industries preferred

- Proven ability to lead global, cross-functional teams and drive transformation

- Strong stakeholder management across executive leadership, product, and clients

Educational Background :

- PhD in a relevant technical or quantitative discipline preferred, reflecting the intellectual depth and domain credibility required to lead enterprise AI at platform scale

- Bachelors or Masters degree in Engineering, Computer Science, or a related field is a baseline requirement; advanced degrees from institutions of repute are an advantage

Leadership Competencies :

- AI as a Business Growth Lever : Ability to translate AI from a technology capability into a driver of revenue, differentiation, and enterprise value creation.

- Enterprise Platform & Product Thinking : Ability to build reusable AI capabilities across integrated product suites, avoiding fragmented point solutions and improving scalability.

- Commercial & Market Orientation : Strong ability to link AI to deal wins, pricing power, and verticalized solutions, with a clear understanding of client value drivers.

- Techno-Commercial Orientation : Ability to bridge AI platform depth and market application translating technical capabilities into enterprise value propositions and ensuring AI decisions are grounded in buyer context and business impact

- Entrepreneurial orientation : Demonstrated ability to build from ambiguity, take initiative without waiting for direction, and operate with a founders mindset inside a scaling enterprise

- Prescriptive Advisory Capability : Ability to engage enterprise customers and internal stakeholders with a well-formed point of view leading with recommendations grounded in AI domain expertise and market insight, and building trust through advisory-led engagement over time

- Intellectual Humility and Organizational Awareness : Openness to learning from customers, field teams, and market realities; demonstrated ability to integrate diverse perspectives into AI and product decisions and prioritize collective outcomes over individual visibility

- Execution at Scale : Demonstrated capability to move from strategy to execution across cross functional teams, balancing speed, governance, and measurable business value.

- Change & Talent Leadership : Ability to build and lead high-caliber AI teams, while driving an AI-first mindset across leadership and the broader organization.

Leadership Style :

- High on collaboration and knowledge multiplication : Builds cross-team collaboration and support, and fosters collective learning and knowledge sharing across the organization

- Customer-first philosophy : Strong customer-first orientation, with the ability to balance innovation, delivery quality, and long-term (30+ years) client relationships in enterprise environments.

- Inclusivity and flexibility : Ability to attract, develop, and integrate talent across geographies, functions, and operating contexts.

- Long-term relationship orientation : Ability to sustain strong relationships across internal and external stakeholders, including leadership, teams, partners, and clients.