Job Description Lead the Agentic AI / Automation CoE operating model, including intake, value sizing, prioritization, governance, funding/chargeback approach (as applicable), and performance reporting. Partner with Business Use Case Owners and functional leaders to discover, evaluate, and prioritize opportunities where AI Agents and automation can drive near-term business value (growth, efficiency, risk reduction, and customer/associate experience). Own the product/service offering for Agentic AI and Automation (e.g., reusable components, reference architectures, templates, guardrails, enablement, and support), ensuring it is easy to adopt and scales across lines of business. Translate business goals into clear product requirements and detailed user stories (including acceptance criteria, controls, and non-functional requirements such as security, privacy, resiliency, and auditability). Manage and continuously refine the enterprise backlog and portfolio of agent initiatives; sequence delivery based on value, feasibility, dependencies, and risk. Drive cross-functional delivery with engineering, data, architecture, and platform teams to ensure high-quality, on-time delivery of agent capabilities and use cases. Support best practices and standards for agent development and operations, including prompt and instruction management, tool/API integration patterns, retrieval-augmented generation (RAG) patterns, evaluation/testing, and lifecycle management. Support responsible AI and risk controls in partnership with legal, compliance, information security, and data governance (e.g., data handling, access controls, model risk, human-in-the-loop, safety, and monitoring). Oversee a production support model for agents (SLAs, incident management, change control, observability, drift and quality monitoring, and continuous improvement). Evaluate and manage key platforms and vendors (agent frameworks, orchestration, automation/RPA, evaluation/monitoring, and knowledge/retrieval tools) in partnership with IT and Procurement. Create executive-ready communication, roadmaps, and status updates; translate technical concepts into business language to enable decision-making at all levels. Measure and report on outcomes and adoption (e.g., value realized, time saved, cycle time, quality, reliability, usage, and user satisfaction); adjust strategy based on evidence and feedback. Build organizational capability through enablement—training, playbooks, office hours, and a community of practice—to accelerate adoption and consistent delivery across teams. Stay current on trends in Agentic AI, GenAI, automation, and AI governance; run rapid experiments and pilots to validate new approaches, and integrate learnings into standards and roadmaps. In partnership with the PMO, organize/lead meetings for collaboration and process implementation, status reporting, and presentations, supporting resource and budget management for the CoE and portfolio. Accountable for product performance and the growth and adoption of AI Agents across the organization; shared accountability with Business Use Case Owners for measurable business outcomes. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements Bachelor’s degree in Business Administration, Computer Science, Information Systems, Engineering, Data Science, or a related field. Master’s degree preferred. 7+ years of experience delivering technology products or platforms, including 2+ years in a Product Owner / Product Manager / Solutions Lead role within an Agile environment. 2+ years of experience delivering AI/ML, analytics, and/or Generative AI solutions in production, including stakeholder-driven roadmap management and measurable value realization. Demonstrated experience leading or operating within a Center of Excellence model (AI, automation, analytics, digital, or similar), including intake/prioritization, governance, and enablement. Strong understanding of Agentic AI concepts and architectures (LLMs, tools/function calling, orchestration, RAG/knowledge retrieval, memory, evaluation, and monitoring) and their practical application to business processes. Experience with automation technologies and practices (workflow automation, APIs/integration, and/or RPA) and designing end-to-end human + agent operating models. Working knowledge of enterprise platforms and modern engineering practices: cloud (Azure and/or AWS), data platforms, APIs, CI/CD, DevSecOps, and production support/operations. Strong grasp of responsible AI, security, privacy, and risk management considerations (e.g., data protection, access control, auditability, third-party/vendor risk, and human oversight). Exceptional communication and executive presence—able to influence stakeholders, facilitate decisions, and align leaders around a compelling vision and roadmap. Strategic, systems thinker with strong analytical skills; able to size value, prioritize trade-offs, and adapt strategy based on performance metrics and feedback. Ability to thrive in a highly collaborative, fast-paced environment with ambiguity; strong bias to action and continuous improvement. Certified Scrum Product Owner (CSPO), SAFe POPM, or equivalent product/agile certification. Cloud certifications (e.g., Azure or AWS) and/or practical experience with LLM/agent frameworks (e.g., Semantic Kernel, LangChain, LangGraph, or comparable). Experience implementing evaluation/monitoring frameworks for GenAI/agents (quality metrics, hallucination testing, red teaming, guardrails) and measuring business impact at scale.