AI Technical Program Manager
The ideal candidate should have proven experience managing and delivering AI-related projects, a working understanding of modern AI technologies, and the ability to leverage AI tools to improve project delivery, productivity, and decision-making.
Key Responsibilities
• Lead end-to-end delivery of AI, Generative AI, Analytics, and Intelligent Automation projects from initiation through production deployment.
• Define project scope, schedules, budgets, resource plans, milestones, and success metrics.
• Collaborate with business, product, data science, engineering, security, and operations teams to ensure successful outcomes.
• Manage project risks, dependencies, issues, and stakeholder communications.
• Drive adoption of AI-enabled project management practices, including AI-assisted planning, reporting, documentation, risk tracking, and productivity optimization.
• Partner with technical teams to integrate AI capabilities throughout the SDLC, including requirements analysis, code generation, testing, documentation, and release planning.
• Facilitate business workshops, governance reviews, status reporting, and executive steering committee meetings.
• Coordinate user acceptance testing, deployment readiness, change management, and business adoption activities.
• Ensure compliance with organizational governance, security, privacy, and Responsible AI requirements.
• Driving organizational change and adoption for AI-enabled business processes. Required Experience & Skills
• 10-14+ years of experience in Project Management, Program Management, Technology Delivery, or Digital Transformation.
• Minimum 2+ years of experience delivering AI, Generative AI, Agentic AI, Data Science, Analytics, or Intelligent Automation projects.
• Familiarity with AI-enabled SDLC tools such as GitHub Copilot, Claude Code, Antigravity, AI coding assistants, automated testing, and AI-driven project management tools.
• Working knowledge of AI, Machine Learning (ML), Generative AI, Large Language Models (LLMs), AI agents, data platforms, APIs, and cloud-based AI services.
• Understanding of LLMOps (optional MLOps), AI evaluation frameworks, model observability, and lifecycle management.
• Familiarity with RAG architectures, vector databases, prompt engineering concepts, AI agents, and orchestration frameworks.
• Knowledge of AI cost governance (AI FinOps), Responsible AI, Compliance, and enterprise AI operating models.
• Proficiency with Jira, Azure DevOps, or similar project management platforms.
• Proven track record delivering enterprise-scale technology initiatives involving multiple stakeholders and cross-functional teams.
• Strong stakeholder management, communication, leadership, and problem-solving skills.
• Experience with Agile, Scrum, or hybrid delivery methodologies.
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