Why This Role Stands Out
As the VP of AI Center of Excellence, you will spearhead transformative AI initiatives, including Generative and Agentic AI, from a remote US location, driving innovation across the enterprise. This impactful leadership role is perfect for a visionary strategist ready to shape the future of AI and advance a cutting-edge platform. Apply now to lead this exciting journey of AI-driven transformation!
Quick Overview
Job Description
Role - VP of AI Center of Excellence (CoE)
Location: US Remote
Role Overview
The VP of AI CoE will lead the strategic development, execution, and scaling of AI initiatives across the enterprise, with a strong focus on Generative AI, Agentic AI systems, and cloud-native architectures. This role is pivotal in transforming SDLC and business operations through AI-driven innovation, ensuring alignment with organizational goals, and fostering a culture of responsible and scalable AI adoption.
The role also includes oversight of internal platform development for flagship products such as CoCo.
Key Responsibilities
Strategic Leadership & Vision
- Define and execute the enterprise-wide AI strategy, aligning with business objectives and innovation roadmaps.
- Lead the development of Agentic AI and Generative AI systems, including autonomous agents and orchestration frameworks.
- Establish and evolve the AI Center of Excellence (CoE) operating model, governance, and engagement frameworks across the organization to support all industry sectors and geographies.
Technology & Architecture
- Oversee the design and deployment of AI solutions leveraging AWS, Azure, and Google Cloud Platform cloud services.
- Ensure scalable, secure, and compliant AI infrastructure, integrating with existing cloud and data platforms.
- Champion the adoption of CoCo with multi-agent systems across delivery projects and client engagements.
- Guide the development and evolution of CoCo, the SDLC optimization platform, ensuring it leverages Agentic AI to streamline software development workflows.
Innovation & Use Case Development
- Identify high-impact AI use cases across business units and lead pilot programs to validate and scale solutions.
- Collaborate with automation, digital engineering, and data teams to build reusable AI components and data products.
- Drive continuous improvement through experimentation, feedback loops, and performance optimization.
Talent Development & Team Leadership
- Build and mentor a multidisciplinary team of AI engineers, data scientists, and solution architects.
- Foster a culture of innovation, ethical AI practices, and cross-functional collaboration.
- Develop internal training programs and partnerships with the Learning team to increase AI literacy across the organization.
Stakeholder Engagement & Communication
- Act as the primary AI evangelist across the organization, engaging with clients’ C-suite executives, business leaders, and external partners.
- Translate complex AI concepts into compelling business value narratives for executive stakeholders.
- Represent the company in industry forums, conferences, and thought leadership platforms.
Qualifications
- 15+ years of total experience in technology, with at least 5 years of experience in AI/ML and leadership roles.
- Proven track record of deploying enterprise-grade AI systems, particularly Generative AI and Agentic AI solutions.
- Deep expertise in cloud platforms, including AWS, Azure, and Google Cloud Platform.
- Strong expertise in vector databases and MLOps.
- Strong understanding of AI governance, data strategy, and ethical AI frameworks.
- Excellent communication, stakeholder management, and strategic thinking skills.
- Experience with industry-leading CRM systems, including Salesforce.
Additional Requirements
Traditional AI Engineering
- Should have hands-on experience building AI applications and AI/ML models.
- Exposure to leading LLM technologies including Claude, Amazon Nova, and OpenAI, across on-premises and cloud environments.
- Strong experience with RAG (Retrieval-Augmented Generation) models and architectures.
- Proven ability to leverage AI to develop practical solutions for real-world business problems.
- Strong customer-facing and client engagement skills.
- Demonstrated ability to work effectively with cross-functional teams.
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