Role: Senior Project Manager, Artificial Intelligence
Project Planning & Execution:
- Lead end-to end AI project delivery from requirements gathering, feasibility analysis, and design to implementation and post-deployment optimization.
- Define clear project scope, timelines, milestones, and deliverables in alignment with business objectives.
- Manage crossfunctional teams including data scientists, ML engineers, software developers, and business analysts.
- Oversee the integration of AI solutions into existing systems or products.
Stakeholder Management:
- Act as the main liaison between technical teams and business stakeholders.
- Communicate project status, risks, and dependencies to senior management and clients.
- Translate technical outputs into business insights and actionable strategies.
Technical & Strategic Alignment:
- Work closely with AI architects and data teams to ensure data availability, quality, and governance.
- Support model lifecycle management including model training, validation, deployment, and monitoring.
- Identify opportunities for applying AI/ML to automate processes, improve decision-making, or enhance customer experience.
- Ensure compliance with AI ethics, data privacy, and regulatory standards (e.g., GDPR, CCPA).
Governance & Reporting:
- Develop project documentation including charters, roadmaps, SOWs, and post-implementation reports.
- Track KPIs and project performance metrics to evaluate impact and return on investment (ROI).
- Manage project budgets, resources, and vendor relationships.
Project Management: PMP (Project Management Professional) certification is highly required.
Agile Methodologies: Certified ScrumMaster (CSM), SAFe Agilist (SA), or similar Agile certification.
AI/ML (Beneficial): Certifications in AI/ML from major cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate) are a significant advantage.
