Job Description

We are seeking an Agile AI Project Manager to lead the planning, execution, and delivery of AI-driven initiatives that enhance our data and analytics ecosystem.

This role serves as the strategic link between business stakeholders and technical teams, ensuring AI solutions align with the comapny's business objectives and deliver measurable value.


The AI Project Manager will oversee the end-to-end lifecycle of AI projects--from requirement gathering and solution design to deployment and adoption. Responsibilities include defining project scope, managing timelines, coordinating cross-functional teams (data scientists, engineers, solution architects), and ensuring adherence to governance, quality, and ethical AI standards. The role also involves prioritizing features, monitoring performance metrics, and ensuring AI models and data pipelines deliver accurate, actionable insights.

EXPERIENCE

1.AI & Data Project Delivery: Minimum of 8 years of experience in managing end-to-end AI/ML or advanced analytics projects (from discovery to production). Experience with MLOps practices (CI/CD for ML, model monitoring, retraining workflows). Exposure to AI/ML tools and platforms (Azure ML, AWS SageMaker, GCP Vertex AI). Experience in Gen AI and Agentic AI projects


2.Data & Technology: Experience in data-driven projects (data engineering, data warehousing, or analytics). Familiarity with data governance, quality, and security frameworks. Understanding of cloud environments (Azure, AWS, GCP) and containerization (Docker, Kubernetes).


3.Project & Program Management: 8+ years in project management, preferably in AI, data, or digital transformation. Experience with Agile/Scrum and hybrid delivery models. Strong background in budgeting, resource planning, and vendor management.


4.Business & Strategy: Experience in translating business problems into AI use cases with measurable ROI. Proven ability to manage executive stakeholders and drive adoption. Exposure to change management and organizational readiness for AI.


5.Governance & Compliance: Experience implementing Responsible AI practices (bias, fairness, explainability). Familiarity with regulatory compliance (GDPR, CCPA, AI Act) and risk management.


6.Leadership & Collaboration: Leading cross-functional teams (data scientists, engineers, product owners). Managing third-party vendors or partners for AI solutions. Driving continuous improvement in delivery processes.


7.Preferred / Nice-to-Have: Domain experience (e.g., properties,food, real estate, Shared services etc). Certifications: PMP, PRINCE2, Agile, or AI/ML-related certifications.