Key Responsibilities:

- Strategic Leadership: Develop and execute the overall AI strategy and roadmap, aligning with business objectives and growth targets.

- Project Oversight: Manage the end-to-end lifecycle of AI projects, from ideation and design to implementation and performance analysis, ensuring timely delivery and alignment with business goals.

- Financial Management: Oversee AI-related budgets, forecasts, and expenditures, ensuring profitability and operational efficiency.

- P&L Ownership: Manage the P&L for AI-related products and services, balancing innovation with cost control to meet financial targets.

- Team Leadership: Lead, mentor, and managing a high-performance team of AI engineers, data scientists, and researchers, fostering a culture of continuous learning and improvement.

- Cross-Functional Collaboration: Work closely with engineering, data analytics, product, and business units to implement AI solutions at scale.

- Ethical Compliance: Ensure the responsible and ethical deployment of AI technologies in accordance with industry standards and regulations.

- Innovation Identification: Identify opportunities for AI innovations that drive growth and operational efficiency.

- Stakeholder Communication: Present AI project outcomes, business impacts, and new opportunities to executive leadership and stakeholders.

- External Engagement: Build and nurture relationships with external partners, vendors, and research institutions to stay at the forefront of AI trends and technologies.

Qualifications:

- Experience: Minimum of 20 years IT industry experience with 10+years in AI/technology, with at least 5 years in a leadership or management role.

- P&L Management: Proven experience in managing P&L for technology or AI-driven products/services.

- Technical Expertise: Strong proficiency in AI technologies, including Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision.

- Financial Acumen: Solid understanding of the commercial and financial aspects of AI projects, including cost management, profitability, and ROI measurement.

- Project Delivery: Experience in scaling AI initiatives and delivering impactful business results.

- Communication Skills: Excellent ability to present complex AI concepts to non-technical stakeholders.

- Leadership Skills: Demonstrated experience in building, motivating, and managing high-performing teams.

- Ethical Awareness: Knowledge of AI ethics, data privacy, and regulatory issues is highly preferred.

Preferred Qualifications:

- Educational Background: Bachelor's or master's degree in computer science, Engineering, or a related field.

- Industry Experience: Experience in industries such as automotive, healthcare, or retail, where AI-driven personalization and predictive analytics are redefining customer experiences and profitability.

- MLOps Knowledge: Familiarity with MLOps methodologies to streamline the process of moving data-heavy applications from development to robust production deployments.

- Cloud Platforms: Experience with cloud platforms and their integration with AI/ML tools.