Technical Project Manager –Services Delivery – AI & Data

Technical Project Manager – Professional Services Delivery – AI & Data

Role Summary

The Technical Project Manager plans and delivers customer-focused technology projects from initiation through closure. The role ensures projects meet agreed scope, schedule, budget, quality, and customer expectations while coordinating technical teams and managing internal and external stakeholders.

Key Responsibilities:

• Plan and manage projects from initiation to closure.
• Define scope, milestones, schedules, budgets, resources, and deliverables.
• Coordinate technical teams, partners, and suppliers to ensure timely execution.
• Manage internal and external stakeholders through regular communication, status reviews, and expectation alignment.
• Track progress, risks, issues, dependencies, and changes, and drive timely resolution.
• Ensure project delivery follows agreed quality, governance, and contractual requirements.
• Monitor project financials, resource utilization, and forecasts.
• Lead customer meetings, governance reviews, and escalations.
• Maintain accurate project documentation and provide clear status reports.
• Support a smooth transition to operations and complete project closure activities.Required Qualifications
• Bachelor’s degree or equivalent practical experience.
• Proven experience managing technology or professional services projects.
• Good understanding of project management methods, tools, and governance.
• Strong communication, organization, problem-solving, and stakeholder management skills.
• Ability to work with cross-functional and geographically distributed teams.
• PMP, PRINCE2, Agile, Scrum, or similar certification is preferred.
• Knowledge of cloud, infrastructure, application, or digital transformation projects is an advantage.Core Skills:
• Project planning and execution
• Internal and external stakeholder management
• Risk, issue, and change management
• Financial and resource tracking
• Customer communication and presentation
• Team coordination and leadership through influenceAI & Data Skills:
• Understanding of AI, machine learning, generative AI, and common business use cases.
• Knowledge of data platforms, data lakes, warehouses, databases, analytics, and business intelligence.
• Experience coordinating data engineering, data science, ML engineering, application, cloud, and security teams.
• Ability to manage AI and data project scope, milestones, dependencies, risks, costs, and measurable business outcomes.
• Familiarity with data quality, governance, privacy, security, responsible AI, and regulatory requirements.
• Understanding of the AI lifecycle, including data preparation, model development, testing, deployment, monitoring, and adoption.
• Exposure to platforms such as Azure AI, AWS AI/ML, Google Cloud AI, Databricks, Snowflake, or similar technologies is preferred.