AI, Copilot, and Innovative Solutions Lead

Overview

Key Responsibilities

• AI Strategy & Roadmap: Develop and drive a comprehensive AI innovation strategy for the organization. Identify opportunities where AI (including generative AI, machine learning, and autonomous agents) can solve problems or create new business value. Define an AI roadmap that aligns with company goals and outline the short- and long-term vision for AI integration. This includes championing Copilot technologies and intelligent agent solutions as part of our strategic initiatives.
   
• Emerging Technology Exploration: Continuously monitor and analyze advancements in AI, machine learning, and related technologies. Stay up-to-date with the latest trends in the industry, including keeping a pulse on Microsoft’s AI announcements from events like Microsoft Build to ensure the company remains at the forefront of innovation. Evaluate emerging tools (e.g. new AI frameworks, Copilot features, AI agent platforms) for their potential impact and provide recommendations on their adoption.
   
• Innovative Solution Development: Lead the ideation, prototyping, and development of innovative AI solutions. This involves spearheading proof-of-concept projects to showcase how AI and Copilot-powered features can create business value. For example, you might oversee the creation of AI-driven assistants or agents that personalize user experiences or automate internal processes. You will plan and execute the deployment of these solutions, ensuring they are aligned with our technical infrastructure and strategic objectives.
   
• AI Integration & Deployment: Oversee the integration of AI models and Copilot/agent technologies into existing products, services, and workflows. Work closely with cross-functional teams (engineering, product, IT, operations) to implement AI capabilities in a scalable, reliable manner. This may include integrating conversational AI agents into customer-facing applications or embedding AI analytics into internal tools. Ensure that AI deployments meet business requirements and adhere to best practices for performance and security.
   
• Copilot & AI Assistant Adoption: Champion the adoption of AI assistants (like Microsoft 365 Copilot or similar AI copilots) and intelligent agents throughout the organization. Identify use cases where these tools can boost productivity or decision-making, and lead initiatives to implement them. This includes configuring or customizing AI assistant solutions to fit our business needs and training employees on their effective use. By doing so, you’ll help teams work smarter and take full advantage of modern AI capabilities.
   
• Stakeholder Collaboration & Evangelism: Act as the evangelist for AI innovation within the company. Work closely with stakeholders at all levels – from end users and project teams to senior executives – to promote understanding of AI technologies and their benefits. Communicate complex AI concepts in clear, non-technical terms to build buy-in and enthusiasm. You will share success stories, demonstrate prototypes, and highlight how AI (e.g. Copilot scenarios) can solve specific business challenges, thereby fostering a culture open to experimentation and change.
   
• Training & Best Practices: Develop and deliver training programs and documentation to ensure teams are equipped to use new AI tools and solutions. Guide colleagues in AI best practices, including principles of machine learning, effective “prompt engineering” for AI copilots, and how to interpret AI outputs responsibly. Establish standards and ethical guidelines for AI usage (e.g. data privacy, avoiding bias), and ensure the organization’s AI efforts adhere to legal and ethical considerations. Mentor internal teams and cultivate in-house AI talent by sharing knowledge and encouraging continuous learning.
   
• Performance Tracking & Optimization: Define key metrics to assess the impact of AI initiatives on the business (such as efficiency improvements, cost savings, revenue growth, or customer satisfaction). Measure and track the outcomes of AI/ML implementations to demonstrate tangible benefits. Use data and feedback to continuously refine AI models and solutions for better accuracy, performance, and user adoption. If a solution underperforms, iterate on the design or retrain models to improve results. Regularly report on AI project performance and lessons learned to stakeholders and adjust the strategy accordingly.
   
• Strategic Leadership & Governance: Provide strategic thought leadership on AI across the organization. Advise senior leadership on emerging AI opportunities, potential risks, and recommended investments or partnerships. Develop business cases and roadmaps for AI projects, outlining resource needs, timelines, and expected business impact. Ensure proper governance of AI projects by establishing processes for project selection, risk assessment, and compliance with IT policies. In this leadership role, you will also liaise with external partners or vendors as needed, and represent the company’s AI strategy in meetings, industry forums, or client discussions.

Required Skills and Qualifications

• Education & Background: Bachelor’s degree (preferred Master’s) in Computer Science, Data Science, Artificial Intelligence, or a related field. Strong foundational knowledge of machine learning algorithms, AI techniques, and software development is required. An advanced degree or continuous education in AI/ML is a plus.
   
• Experience: 5+ years of experience in roles involving AI/ML development or technology innovation, with a proven track record of delivering AI-powered projects from concept to production. Experience leading innovation initiatives or digital transformation projects is highly desirable. Exposure to implementing AI solutions like chatbots, recommendation systems, or process automation in a business setting will be beneficial.
   
• Technical Proficiency: Hands-on experience with modern AI and data science tools. Proficiency in programming (Python, R, or similar) and familiarity with machine learning frameworks such as TensorFlow or PyTorch is expected ⁴. Experience working with cloud AI platforms (e.g., Microsoft Azure AI services, AWS SageMaker, or Google Cloud AI) and APIs (including experience with large language models or OpenAI technologies) is highly valued. Knowledge of building or integrating conversational agents or AI Copilot-style applications is a strong plus.
   
• Microsoft Ecosystem Knowledge: Solid understanding of Microsoft’s AI and productivity ecosystem will be an advantage. This could include experience with Azure OpenAI Service, Power BI (with AI features), Power Virtual Agents, or Microsoft 365 Copilot capabilities. The ideal candidate can rapidly learn and utilize new Microsoft tools announced at events like Ignite or Build, integrating them into our solutions to keep us technologically current. (Note: Specific Microsoft tool experience is not mandatory, but a demonstrated ability to quickly adopt such tools is essential.)
   
• Leadership & Communication: Excellent communication and interpersonal skills, with the ability to engage and influence stakeholders across the organization. You should be adept at translating complex technical information into business insights and actionable recommendations. Strong leadership and team management skills are needed to inspire multidisciplinary teams and drive projects forward. Prior experience in leading a team or cross-functional project group in a fast-paced environment is preferred.
   
• Innovative & Analytical Mindset: A passion for innovation, creativity in problem-solving, and a forward-thinking mindset. You continuously seek out new ideas and emerging technologies, and you’re comfortable experimenting and learning from failures. Strong analytical and strategic thinking abilities are required to assess the potential of AI initiatives and to make data-driven decisions. Ability to balance big-picture vision with attention to detail in execution.
   
• Adaptability and Continuous Learning: Given the rapid evolution in the AI field, the candidate must be highly adaptable and committed to continuous learning. This role requires someone who proactively keeps their skills and knowledge up-to-date, whether by following industry news, obtaining relevant certifications, or participating in professional communities. Demonstrated enthusiasm for attending tech conferences, workshops, or trainings (e.g., Microsoft Build, Ignite, or academic AI conferences) will be seen as a positive.
   
• Ethical Judgment: Deep appreciation for the ethical implications of AI. Familiarity with AI ethics, data privacy regulations, and responsible AI principles is important to ensure our solutions are trustworthy and compliant. The candidate should be able to identify potential ethical or bias issues in AI systems and guide the team in mitigating them.