Lead AI Project Manager

We are looking for an experienced AI Project Manager to lead the end-to-end delivery of high-impact AI initiatives across energy solutions, engineering, manufacturing, retail, and supply chain optimization.

You will manage cross-functional teams building agentic AI systems, computer vision solutions, generative AI applications, and intelligent workflow automations, ensuring agile delivery, ethical AI adoption, and measurable business outcomes such as revenue uplift, cost reduction, and productivity improvement.

Key Responsibilities

• Lead planning, execution, and delivery of AI/ML projects from ideation to production
• Define project scope, timelines, budgets, risks, and success metrics (ROI, accuracy, business impact)
• Manage cross-functional teams including Data Scientists, AI Engineers, MLOps, and Developers
• Implement Agile/Scrum methodologies and ensure timely, high-quality delivery
• Track KPIs such as model performance, ROI, and operational impact; present updates to senior leadership
• Ensure compliance with AI governance, data privacy, security, and ethical AI standards
• Drive integration of open-source and enterprise tools (e.g., workflow automation platforms, LLM frameworks, cloud and edge AI solutions)
• Coordinate with technology partners and vendors as needed

Required Skills & Experience

• 10+ years of overall project management experience (PMP / Agile certification preferred)
• 5+ years managing AI/ML projects, preferably in industrial or manufacturing environments
• Strong understanding of modern AI concepts:
• Agentic AI
• Generative AI (RAG, fine-tuning)
• Computer Vision
• MLOps pipelines
• Experience with API-driven and event-driven architectures
• Solid knowledge of cloud platforms (IaaS, PaaS), containerization, and microservices
• Hands-on experience defining AI governance frameworks (model approval, bias, explainability, transparency, data privacy & security)
• Excellent stakeholder management, communication, and leadership skills

Preferred Qualifications

• Exposure to industrial AI use cases such as predictive maintenance, inventory optimization, and quality inspection
• Awareness of emerging AI trends including multimodal AI, autonomous agents, and real-time analytics