REQUIRED SKILLS & EXPERIENCE

• 8–12+ years of experience in IT project/program management with at least 3–5 years in AI/ML-related projects.
• Proven track record of managing Generative AI, NLP, LLM, or ML projects in enterprise environments.
• Strong understanding of AI/ML lifecycle (model development, training, fine-tuning, deployment, monitoring).
• Experience with cloud platforms (AWS, Azure, GCP) and AI/ML services.
• Familiarity with tools such as LangChain, Hugging Face, OpenAI APIs, vector databases, RAG pipelines is a strong plus.
• Demonstrated experience in Agile/Scrum methodologies, Jira/Confluence.
• Strong leadership, communication, and stakeholder management skills.
• Knowledge of AI governance, data privacy, and ethical AI practices.
• PMP/PRINCE2/Agile certifications preferred.

EDUCATIONAL QUALIFICATIONS

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
• Certifications in Project Management (PMP, PRINCE2, Agile).
• AI/ML certifications (AWS, Azure, GCP AI, or equivalent) preferred.

ABOUT THE ROLE

We are seeking a Technical Project Manager – Generative AI with deep expertise in managing AI/ML-driven projects, particularly in Generative AI solutions. The ideal candidate will bridge the gap between business stakeholders, data scientists, AI engineers, and software teams, ensuring timely and high-quality delivery of AI initiatives. You will oversee project execution, manage cross-functional teams, and drive the implementation of cutting-edge AI-powered solutions for enterprise-scale use cases.

KEY RESPONSIBILITIES

• Lead and manage end-to-end Generative AI projects, from requirements gathering to deployment and adoption.
• Collaborate with stakeholders to define project scope, objectives, timelines, and deliverables.
• Translate business needs into technical project requirements and align with AI/ML teams.
• Oversee solution design and implementation in Generative AI models (LLMs, NLP, multimodal AI).
• Manage project risks, budgets, and dependencies, ensuring on-time and within-budget delivery.
• Ensure compliance with AI governance, security, and ethical frameworks.
• Drive Agile project management practices, including sprint planning, backlog grooming, and stand-ups.
• Act as the liaison between business, product, data science, and engineering teams.
• Track and report project progress, KPIs, and delivery milestones to leadership.
• Support pre-sales, proposals, and client presentations when required.