AI Product & Program Manager – Generative AI, LLMs, Roadmap Strategy, Agile/SAFe & Governance

Job Summary

Synechron is seeking an AI Product / Program Management Manager with 10+ years of experience to lead the strategy, planning, delivery and governance of enterprise AI initiatives.The role will define AI product roadmaps, manage cross-functional programs, align business objectives with AI solutions and oversee execution from ideation through production. The position requires experience in product management, program delivery, stakeholder engagement, digital transformation and AI/Generative AI technologies.

Software Requirements

Required

• Product management and roadmap-management tools for defining:Product vision and strategyUse-case prioritiesProduct requirementsUser storiesSuccess metricsBusiness cases

• Program and portfolio management tools for tracking:Program plansBudgetsResourcesTimelinesRisksIssuesDependenciesMilestones

• Agile delivery tools used to manage backlogs, sprints, releases, dependencies and delivery reporting.

• Reporting and presentation tools used for executive-level status updates, governance forums, business cases and performance reporting.

• Collaboration and workshop tools used for requirements gathering, stakeholder alignment, executive reviews and cross-functional delivery.

• Data analysis and dashboarding tools used to measure AI adoption, business impact, ROI, operational efficiency and customer outcomes.

• Working knowledge of AI platforms and tools, including one or more of the following:Azure AIAzure OpenAIAWS AI/MLGoogle Vertex AIDatabricksSimilar enterprise AI platforms

• Tools and frameworks used to support AI governance, privacy, security, risk management, compliance and model lifecycle oversight.

Preferred

• Advanced experience with product portfolio, investment and benefits-realization tools.

• Experience with tools supporting AI use-case intake, prioritization, model governance and responsible AI reviews.

• Experience with dashboarding and analytics tools for KPI tracking and executive reporting.

• Experience with vendor-management, procurement and contract-tracking tools.

• Experience with tools that support SAFe, Scrum, Agile planning and enterprise delivery governance.

Overall Responsibilities

Product Strategy and Roadmap

• Define and drive the vision, strategy and roadmap for AI and Generative AI products.

• Identify business opportunities where AI can create measurable value, operational efficiency, improved customer experience or competitive advantage.

• Work with business leaders, clients, product teams and technology teams to assess, prioritize and sequence AI use cases.

• Develop product requirements, user stories, success metrics, business cases and value hypotheses.

• Align product roadmaps with organizational strategy, technology capabilities, data availability, regulatory expectations and delivery capacity.

• Establish clear product outcomes and communicate priorities to all relevant stakeholders.

Program Management and Delivery

• Lead end-to-end delivery of AI initiatives across multiple teams and stakeholder groups.

• Manage program planning, budgeting, resource allocation, timelines, risks, issues, dependencies and delivery milestones.

• Establish governance frameworks that support consistent decision-making, accountability and alignment with organizational objectives.

• Track program progress and provide regular executive-level status updates.

• Coordinate delivery across product, engineering, data, architecture, security, compliance, operations and business teams.

• Ensure AI programs are delivered within agreed scope, budget and timelines, or that changes are formally assessed and communicated.

• Drive issue resolution, escalation management and corrective actions across the program lifecycle.

AI and Technology Leadership

• Collaborate with Data Scientists, AI Engineers, Architects and Business Analysts to define AI-driven solutions.

• Drive the adoption of Generative AI, Machine Learning, NLP, Computer Vision and other relevant AI technologies.

• Evaluate AI platforms, tools and vendors against business needs, technical suitability, security, cost, scalability and support requirements.

• Ensure AI products are designed for scalability, reliability, security, maintainability and regulatory compliance.

• Support decisions related to data readiness, model selection, model lifecycle, integration, deployment and operational support.

• Translate technical risks and constraints into clear business impacts and delivery recommendations.

Stakeholder and Client Management

• Act as the primary interface between business stakeholders, clients and technical teams.

• Facilitate workshops, requirements-gathering sessions, use-case discovery sessions, prioritization forums and executive reviews.

• Communicate program status, risks, issues, dependencies, decisions, outcomes and changes to senior leadership.

• Build alignment across stakeholders with different priorities, levels of technical knowledge and business objectives.

• Manage expectations, negotiate trade-offs and maintain clear communication throughout product and program delivery.

• Capture stakeholder feedback and ensure it is reflected in product decisions and delivery plans.

Governance and Risk Management

• Implement AI governance frameworks covering ethics, compliance, privacy, security, data usage and model risk.

• Monitor risks, issues and mitigation plans across AI programs.

• Ensure adherence to enterprise architecture, data governance and applicable regulatory standards.

• Establish appropriate review points for AI use-case approval, solution design, model evaluation, release readiness and production monitoring.

• Support responsible AI practices, including transparency, explainability, fairness, human oversight and appropriate controls.

• Ensure that production AI solutions have defined ownership, monitoring, support and escalation processes.

Performance and Value Realization

• Define KPIs and success metrics for AI products and programs.

• Measure business impact, ROI, adoption, customer outcomes and operational efficiency improvements.

• Establish mechanisms to track benefits against approved business cases.

• Use data-driven insights to support continuous improvement and product decisions.

• Identify opportunities to improve AI adoption, delivery efficiency, solution quality and business value.

• Report success metrics and value realization to relevant stakeholders and governance forums.

Sustainability Considerations

• Promote responsible and sustainable AI delivery by considering infrastructure efficiency, model utilization, data reuse, operational maintainability and long-term platform costs.

• Encourage reusable AI capabilities and shared services to reduce duplicated development and unnecessary resource consumption.

• Include appropriate environmental, operational and lifecycle considerations when evaluating AI platforms and solution options.

Technical Skills (By Category)

Programming Languages

Essential

• No specific programming language is mandatory for the role.

• Ability to understand AI solution designs, technical dependencies, integration approaches, data requirements and production constraints.

• Ability to work effectively with technical teams and assess the delivery implications of AI implementation choices.

Preferred

• Working knowledge of Python and its use in AI, machine learning or data-processing solutions.

• Familiarity with programming concepts used in APIs, microservices, data pipelines and AI application integration.

Databases and Data Management

Essential

• Understanding of data requirements for AI and Generative AI initiatives.

• Ability to assess data availability, quality, privacy, ownership, access and readiness.

• Understanding of data governance, data lineage, data security and enterprise integration.

• Ability to collaborate with data teams on data ingestion, prep