AI/ML & Technology Delivery
•Lead delivery of AI/ML and Generative AI projects, ensuring timely, high-quality outcomes.
•Oversee data preparation, model development, deployment, and MLOps pipelines.
•Drive delivery of end-to-end solutions that integrate AI components into existing or new applications.
•Collaborate with engineering and product teams to define scalable AI architectures and workflows.
Program & Project Management
•Manage multiple AI and software delivery workstreams simultaneously.
•Maintain program roadmaps, milestones, risk registers, and status reports.
•Develop delivery models, governance structures, and quality frameworks.
•Ensure adherence to timelines, scope, budget, and compliance standards.
Stakeholder & Client Management
•Serve as the primary point of contact for business and technical stakeholders.
•Translate business needs into AI delivery plans, PoC scopes, and implementation strategies.
•Present program updates, metrics, and risks to senior leadership and client executives.
•Maintain strong relationships with customer teams to ensure satisfaction and alignment.
Team Leadership & Collaboration
•Lead cross-functional teams including Data Scientists, ML Engineers, Data Engineers, Developers, QA, and Cloud Engineers.
•Facilitate collaboration between technical and non-technical teams.
•Mentor delivery teams on best practices, execution discipline, and continuous improvement.
Operational & Delivery Excellence
•Ensure AI solutions follow responsible AI principles, data security, and governance standards.
•Implement KPIs, SLAs, and performance dashboards to track model and program health.
•Promote delivery reusability frameworks, automation, and process optimization.
Required Skills & Qualifications
•8+ years of experience in technology or software delivery , including:
•3 years of experience delivering AI/ML or Generative AI programs
•Prior experience leading large-scale IT/software projects
•Strong expertise in Agile, Scrum, and hybrid delivery methodologies.
•Understanding of AI/ML lifecycle, including data engineering, model development, deployment, and monitoring.
•Familiarity with cloud ecosystems (Azure, AWS, GCP) and MLOps tooling.
•Excellent skills in stakeholder communication, executive reporting, and expectation management.
•Proven ability to manage budgets, resource plans, and multi-vendor teams.
•Strong risk management, governance, and escalation handling experience.
