Responsibilities
- Strategy & Leadership
- Define and drive the organization’s vision and strategy for generative AI, ensuring alignment with overall business objectives.
- Identify opportunities for innovation and business value creation through AI-driven insights and solutions.
- Develop and maintain a roadmap for AI adoption, piloting initiatives, and driving adoption across various business units.
- Solution Development & Implementation
- Lead cross-functional teams of data scientists, engineers, product managers, and domain experts to design, build, and deploy generative AI-driven solutions that address key business challenges.
- Develop and maintain an enterprise-wide Generative AI platform, ensuring it is scalable, secure, compliant, and easily accessible to different business units.
- Oversee large-scale AI projects, ensuring technical feasibility, budget management, and timely delivery.
- Guide the development of proof-of-concepts (PoCs) and MVPs, creating scalable AI solutions that can be integrated into the organization’s technology stack.
- Team Building & Management
- Attract, hire, and retain top AI talent, developing an environment that fosters creativity, collaboration, and continuous learning.
- Coach and mentor team members, providing professional development opportunities and skill-building initiatives.
- Establish agile project management practices, promoting high efficiency, accountability, and transparency.
- Stakeholder Engagement
- Collaborate with senior leadership, department heads, and external partners to identify business needs and evaluate AI solution viability.
- Communicate complex AI concepts in clear, business-oriented language to stakeholders at all levels.
- Build and maintain relationships with technology vendors, business lines and other external parties for potential partnerships and co-innovation projects.
- Governance & Ethics
- Define and implement best practices for AI ethics, data privacy, and responsible AI governance.
- Ensure compliance with relevant regulations and internal policies.
- Establish standards and guidelines for model deployment, monitoring, and risk management.
- Performance Measurement & Continuous Improvement
- Develop KPIs and metrics to measure the success, impact, and ROI of AI initiatives.
- Implement processes for ongoing evaluation and optimization of AI models and processes.
- Cultivate a data-driven culture and champion continuous improvement across all AI-related activities.
- Education
- Background in computer science, Machine Learning, Data Science, or a related field preferred. Equivalent experience in AI leadership and innovation may be considered.
- Experience
- 10+ years of experience in AI/ML, data science, or a similar field, with at least 5 years in a leadership role.
- Proven track record of delivering AI solutions (particularly generative models) in complex, high-impact environments.
- Experience managing cross-functional teams and large-scale, transformational projects.
- Technical Expertise
- Proficiency in machine learning, deep learning, NLP, computer vision, and other AI domains.
- Familiarity with the latest generative AI architectures (e.g., Transformer-based models, diffusion models, etc.) and large-language-model frameworks.
- Experience with cloud-based AI platforms (AWS, Azure, GCP) and relevant ML frameworks (TensorFlow, PyTorch, etc.).
- Demonstrated experience in building or integrating AI platforms in an enterprise setting.
- Business Acumen
- Strong understanding of how AI can drive business value, with the ability to connect technical capabilities to strategic objectives.
- Experience in budgeting, project planning, and managing vendor relationships.
- Adept at quantifying business impact and ROI of AI initiatives.
- Leadership & Soft Skills
- Exceptional communication skills, capable of translating complex technical topics into business language.
- Demonstrated ability to lead, motivate, and mentor high-performing teams.
- Strong problem-solving and decision-making abilities with a track record of managing ambiguity.
- Collaborative mindset, capable of building consensus among diverse stakeholders.
- Strategic Thinking: Ability to set a clear vision for AI initiatives that align with overall business goals.
- Innovation & Creativity: Comfortable exploring novel approaches and challenging the status quo.
- Execution Excellence: Track record of taking AI concepts to production, with a focus on quality and scalability.
- Change Management: Skilled in driving organizational change, influencing culture shifts, and instilling a data-driven mindset.
- Risk Management: Adept at identifying and mitigating technical, ethical, and compliance-related risks.
- Collaboration & Influence: Strong interpersonal skills to forge partnerships with internal and external stakeholders.