AI Project Manager
Zensar
AI Project Manager
Zensar
Global IT services for digital transformation
AI Project Manager
Experience: 10–15 Years
Location: Pune / Bengaluru / Hyderabad
Looking for a workplace where people realize their full potential, are recognized for the impact they make, and enjoy the company of the peers they work with? Welcome to Zensar! Read on for more details on the role and about us.
We are seeking an experienced AI Project Manager to lead the delivery and governance of enterprise-scale AI, Generative AI, and Agentic AI initiatives. The ideal candidate will be responsible for managing end-to-end AI program execution, stakeholder engagement, project planning, delivery governance, and cross-functional team coordination to ensure successful deployment of AI-driven business solutions.
The role requires close collaboration with business stakeholders, customers, AI architects, data scientists, AI engineers, platform teams and delivery leadership to translate business objectives into deliverable AI solutions. The candidate should possess strong experience managing GenAI, Machine Learning, Agentic AI, RAG-based applications, AI platform implementations and enterprise AI transformation programs while ensuring delivery excellence, risk management, quality, and customer success.
Skills required to contribute:
Required Skills
10+ years of overall IT experience with at least 4–6 years of project/ program management experience in AI, Data Science, Analytics or Digital Transformation initiatives.
Proven experience managing AI/ML, Generative AI, Agentic AI and Data & Analytics projects from inception to production deployment.
Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Conversational AI, and enterprise AI use cases.
Experience managing cross-functional teams comprising AI Architects, Data Scientists, AI Engineers, MLOps Engineers and Business Analysts.
Expertise in project planning, estimation, resource management, budgeting, tracking and governance.
Experience in Agile, Scrum, Kanban and iterative delivery methodologies.
Strong customer-facing experience, including stakeholder management, project reviews, executive reporting and steering committee presentations.
Ability to drive AI discovery workshops, requirements gathering, solution planning and roadmap definition.
Experience managing risks, dependencies, change requests and delivery escalations across multiple workstreams.
Familiarity with AI lifecycle activities including data preparation, model development, evaluation, deployment, observability, governance and monitoring.
Understanding of Responsible AI, AI governance, security, compliance and enterprise adoption considerations.
Experience coordinating cloud-based AI implementations on Azure, AWS, or Google Cloud Platform.
Strong communication, leadership, negotiation and team management skills.
Ability to manage multiple projects and customer engagements simultaneously while ensuring quality delivery and business outcomes.
We are seeking an experienced AI Project Manager to lead the delivery and governance of enterprise-scale AI, Generative AI, and Agentic AI initiatives. The ideal candidate will be responsible for managing end-to-end AI program execution, stakeholder engagement, project planning, delivery governance, and cross-functional team coordination to ensure successful deployment of AI-driven business solutions.
The role requires close collaboration with business stakeholders, customers, AI architects, data scientists, AI engineers, platform teams and delivery leadership to translate business objectives into deliverable AI solutions. The candidate should possess strong experience managing GenAI, Machine Learning, Agentic AI, RAG-based applications, AI platform implementations and enterprise AI transformation programs while ensuring delivery excellence, risk management, quality, and customer success.
Skills required to contribute:
Required Skills
10+ years of overall IT experience with at least 4–6 years of project/ program management experience in AI, Data Science, Analytics or Digital Transformation initiatives.
Proven experience managing AI/ML, Generative AI, Agentic AI and Data & Analytics projects from inception to production deployment.
Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Conversational AI, and enterprise AI use cases.
Experience managing cross-functional teams comprising AI Architects, Data Scientists, AI Engineers, MLOps Engineers and Business Analysts.
Expertise in project planning, estimation, resource management, budgeting, tracking and governance.
Experience in Agile, Scrum, Kanban and iterative delivery methodologies.
Strong customer-facing experience, including stakeholder management, project reviews, executive reporting and steering committee presentations.
Ability to drive AI discovery workshops, requirements gathering, solution planning and roadmap definition.
Experience managing risks, dependencies, change requests and delivery escalations across multiple workstreams.
Familiarity with AI lifecycle activities including data preparation, model development, evaluation, deployment, observability, governance and monitoring.
Understanding of Responsible AI, AI governance, security, compliance and enterprise adoption considerations.
Experience coordinating cloud-based AI implementations on Azure, AWS, or Google Cloud Platform.
Strong communication, leadership, negotiation and team management skills.
Ability to manage multiple projects and customer engagements simultaneously while ensuring quality delivery and business outcomes.
Digital solutions and IT services company that partners with global organizations to drive digital transformation. Its offerings include intelligent automation, analytics, hyperconverged infrastructure, and digital application development and maintenance, delivered through long-term contracts, project-based engagements, and managed services. Indigo Slate handles virtual event creation. Zensar’s Living AI integrates artificial intelligence into business processes to boost outcomes. Unlike many competitors, it emphasizes reducing capital expenditure (Capex) and operating expenditure (Opex), simplifying vendor management, and improving efficiency through automation. The overall goal is to help clients adapt to the digital landscape, optimize technology infrastructure, and achieve higher operational efficiency.
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