Artificial Intelligence Project Manager

Technical Project Manager to lead the end to end delivery of advanced Generative AI initiatives experience range 12+ yrs. Candidate should have practical handson experience implementing Retrieval Augmented Generation RAG pipelines Large Language Models LLMs and Microsoft Copilot solutions within the Azure ecosystem

The candidate must be dynamic committed and capable of preparing tracking managing and driving the projects Excellent communication skills and experienced in handling multivendor multi stakeholder environments

Primary skills

• Lead the full lifecycle of GenAI projects from proofofconcept PoC to deployment on Azure managing scope timelines and budget
• Supervise technical teams in developing RAG pipelines LLMbased assistants and agentic workflows
• Coordinate the implementation and extension of Microsoft 365 Copilots and custom Copilot Studio agents.
• Manage GenAIspecific risks including hallucination mitigation data privacy PII masking and Responsible AI guardrails ensuring compliance with internal AI governance.
• Should have executed large scale Migrations Implementations.
• Experienced in driving major IT projects managing multiple priorities simultaneously setting timelines holding people accountable and delivering projects on time and on budget.
• Experienced in Azure Services technologies.
• Expertise in planning and managing multiple stakeholders including client offshore and cross functional teams to deliver the projects.
• Understanding of GenAI RAG LLM Azure OpenAI Azure AI Studio Copilot.
• ADO or any project Management tools.

Secondary Skills

• Strong communication skills with effective and efficient stakeholder management.
• Excellent time management prioritization and organizational skills
• Must have experience working with tight deadlines and handling escalations
• Manage Governance collate projects status report at regular intervals to leadership team.
• DailyWeekly cadence on project program reviews and reporting to internal stakeholders.
• Track report schedule and cost variance across projects.
• Identification of issues risks and track till closure or mitigation resolution of all cloud transformation projects