Chief AI Officer

Dynamic Search Consulting (DSC) is a boutique retained executive search firm that specializes in VP and C-level placement nationally across various functions and verticals. This posting is not for a specific search but for the type of candidate profile we frequently recruit for, so please apply so we can get connected and keep you in mind as relevant retained searches arise.Key ResponsibilitiesThe following information is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all duties, responsibilities, or required skills.Define and lead the company’s enterprise-wide AI strategy, roadmap, investment priorities, and execution plan in alignment with the company’s growth objectives and private equity value-creation strategy.Partner with the CEO, Board, private equity sponsor, Product, Engineering, Sales, Customer Success, Finance, and other senior leaders to identify and prioritize the highest-impact applications of artificial intelligence.Lead the development and commercialization of AI-powered products, features, capabilities, and platform enhancements that strengthen differentiation, customer value, retention, and revenue growth.Identify opportunities to embed AI throughout internal workflows, including sales, marketing, customer support, engineering, finance, operations, analytics, and knowledge management.Establish a disciplined framework for evaluating AI opportunities based on commercial impact, implementation complexity, data readiness, customer demand, scalability, cost, and measurable return on investment.Build and oversee the company’s AI technology ecosystem, including foundation models, machine learning infrastructure, data architecture, retrieval systems, automation tools, AI agents, model orchestration, and third-party AI platforms.Partner closely with Product and Engineering leadership to determine appropriate build-versus-buy decisions and ensure AI initiatives integrate effectively with the company’s existing SaaS platform and technology architecture.Establish AI governance, security, privacy, model-risk, responsible AI, and compliance standards in partnership with Legal, Security, and Technology leadership.Develop systems for measuring AI adoption, productivity improvement, customer impact, monetization, gross margin enhancement, operating leverage, and overall return on AI investments.Evaluate emerging AI technologies, vendors, partnerships, acquisition targets, and strategic opportunities that could accelerate the company’s competitive position.Recruit, develop, and lead a high-performing team across AI engineering, machine learning, data science, applied AI, and related technical disciplines.Educate executive leadership, employees, customers, and Board members on evolving AI capabilities, limitations, opportunities, competitive threats, and strategic implications.Serve as the company’s senior AI thought leader while translating rapidly evolving technology into practical business outcomes and sustainable enterprise value creation.Ideal CandidateProven Chief AI Officer, Chief Technology Officer, Chief Data Officer, VP of AI, Head of AI, Head of Machine Learning, or senior artificial intelligence leadership experience within a SaaS, software, technology, or data-driven organization.Demonstrated experience developing and executing enterprise-level AI strategies that resulted in measurable revenue growth, product differentiation, productivity improvements, cost savings, or operational leverage.Strong understanding of generative AI, large language models, machine learning, natural language processing, AI agents, retrieval-augmented generation, model evaluation, and modern AI infrastructure.Experience integrating AI capabilities into commercial SaaS products and successfully moving AI initiatives from experimentation into scalable production environments.Strong product orientation with the ability to translate technical capabilities into compelling customer use cases, differentiated product offerings, and monetizable solutions.Experience working within a private equity-backed, growth-stage, or transformation-oriented organization is strongly preferred.Demonstrated ability to evaluate AI investments based on ROI, adoption, scalability, customer value, gross margin impact, and enterprise value creation.Strong understanding of data architecture, APIs, cloud infrastructure, security, data governance, privacy, and the technical foundations required to deploy enterprise AI responsibly.Experience evaluating and working with leading AI platforms, foundation models, cloud providers, data platforms, and emerging AI technologies.Strong leadership experience building and developing teams across AI engineering, machine learning, data science, product, and applied research.Ability to communicate complex AI concepts clearly to CEOs, Boards, investors, customers, commercial leaders, and non-technical stakeholders.Experience supporting M&A due diligence, technology evaluations, AI-related acquisitions, post-acquisition integration, or portfolio-wide AI initiatives is a plus.Bachelor’s or advanced degree in computer science, artificial intelligence, machine learning, engineering, mathematics, data science, or a related field is preferred.Leadership StyleWe’re looking for a Chief AI Officer who is visionary but highly execution-oriented, technically sophisticated but commercially minded, and capable of separating meaningful AI opportunities from short-term hype. This leader should bring intellectual curiosity, urgency, strong business judgment, and a relentless focus on measurable outcomes.The ideal candidate will be equally comfortable discussing model architecture with engineers, product strategy with customers, operational efficiencies with functional leaders, and enterprise value creation with the CEO, Board, and private equity sponsor. This executive should be willing to experiment quickly while maintaining disciplined standards around security, privacy, governance, scalability, and return on investment.Success in this role will be measured by the successful commercialization of AI-powered products, increased customer adoption, measurable revenue contribution, improved internal productivity, greater operating leverage, accelerated product innovation, stronger competitive differentiation, disciplined AI governance, and demonstrable enterprise value creation from the company’s AI strategy.