Vice President of Engineering (AI)

Job Title: Vice President of Engineering (AI)

Key Responsibilities:

• Take charge of AI and Software engineering, architecture, and R&D for cutting-edge digital solutions.
• Lead a multidisciplinary team of AI engineers and software developers to create next-generation AI and data-driven solutions.
• Drive innovation by incubating new solution ideas and leading R&D efforts in collaboration with cross-functional teams to define architectures, data models, and analytics for AI systems. Promote experimentation and exploration of emerging AI techniques.
• Define the AI and software architecture, selecting the appropriate technologies from open-source and commercial options. Choose optimal deployment models, whether cloud-based, on-premises, or hybrid, ensuring seamless integration with existing data management and analytics systems.
• Design and implement a comprehensive enterprise-level architecture for AI solutions, covering everything from envisioning and building to deploying and operationalizing machine learning and AI pipelines.
• Infuse generative AI capabilities across AI solutions from concept to market, ensuring innovation in AI-based products.
• Collaborate with product teams to develop roadmaps for achieving product-market fit and the commercialization of AI solutions.
• Foster relationships with technical stakeholders at key clients, offering expert insight on applying digital transformation to meet their business objectives.
• Engage in research and testing to enhance existing models and propose novel AI approaches.
• Collaborate with various teams to integrate generative AI into real-world applications.
• Apply a product-focused mindset, ensuring development plans, engineering practices, modular architecture, and continuous feedback loops for evolving AI solutions.
• Mentor and guide AI and cloud architects, engineers, and developers, promoting thought leadership and continuous innovation while staying informed about the latest AI trends.
• Oversee AI model development, selecting suitable tools, frameworks, and platforms for optimal performance.
• Contribute to the AI solutions strategy within targeted industry sectors.
• Support presales and delivery efforts, focusing on IT engineering and security aspects.
• Lead intellectual property management, overseeing patents, trademarks, and copyrights, while conducting audits to assess the integrity and value of IP assets.

Essential Qualifications & Experience:

• Over 15 years of proven experience leading global teams of 20+ professionals with diverse skill sets, including solution architects, data scientists, technical architects, and developers.
• Expertise in solution architecture (including functionality, features, and AI workflow impact).
• Technical architecture expertise, including data flow, technology integration, scalability, and security considerations.
• In-depth experience with cloud platforms such as AWS or Azure.
• Proven success in collaborating with senior business and technology stakeholders.
• Experience in building large-scale AI products or platforms for NLP, speech, computer vision, or recommendation systems serving millions of users.

Desired Skills & Attributes:

• Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; an advanced degree (Master’s or Ph.D.) is preferred.
• Technical Expertise:
• Proven leadership in AI and machine learning engineering, managing complex projects and leading teams.
• Deep knowledge of AI technologies (including GenAI, deep learning, NLP, computer vision, RAG, and Knowledge Graph), as well as proficiency in programming languages (e.g., Python, R) and AI frameworks (e.g., TensorFlow, PyTorch).
• Expertise in architecting AI solutions using APIs and SDKs to leverage foundational models and LLMs.
• Experience with cloud solution engineering, with a preference for AWS or Azure.
• Skills in cloud security, disaster recovery, storage, networking, virtualization, containerization, orchestration, Linux, web services, APIs, and DevOps.
• Experience in building and deploying scalable, cloud-native applications and platforms.
• Leadership Skills: Proven ability to lead and mentor engineering teams with strong interpersonal and management skills.
• Project Management: Experience managing AI projects with an emphasis on delivering high-quality outcomes.
• Innovation: A portfolio showcasing innovative AI solutions, including patents, publications, and conference presentations, is a plus.
• Communication: Excellent written and verbal communication skills, with the ability to explain complex technical topics to diverse audiences.