Role Overview
The Technical Manager – AI and Data is responsible for leading and managing AI and data-related initiatives, ensuring they are delivered on time, within scope, and within budget. This role sits at the intersection of technology and business, requiring both deep technical expertise and strong stakeholder management capabilities. The manager oversees planning, resource allocation, and progress tracking while ensuring smooth collaboration between internal teams and external partners. Key responsibilities include risk management, executive communication, and ensuring all deliverables meet rigorous quality standards aligned with organizational strategy.
Key Responsibilities
Project Leadership & Delivery
- Lead end-to-end management of AI and data initiatives, from requirements gathering through deployment and post-launch review.
- Develop comprehensive plans including scope definition, milestone timelines, resource allocation, and budget frameworks.
- Monitor and evaluate performance using appropriate KPIs, providing timely reporting on progress to leadership.
- Drive accountability across all workstreams to ensure deliverables are met on schedule and to the agreed quality standard.
Stakeholder & Partner Management
- Conduct regular status updates and executive briefings to senior stakeholders and sponsors.
- Manage relationships with internal cross-functional teams and external partners, system integrators, and vendors.
- Facilitate effective collaboration between business units and technical teams, bridging communication gaps.
- Act as the primary escalation point for issues and client-facing concerns.
Risk & Issue Management
- Proactively identify, assess, and manage risks throughout the full lifecycle.
- Develop mitigation strategies and contingency plans, escalating critical issues to appropriate decision-makers.
- Maintain a live risk register and issue log, tracking resolution actions and ownership.
Technical & Strategic Alignment
- Ensure all AI solutions and data initiatives align with business requirements, strategic objectives, and compliance standards.
- Drive adoption of best practices and methodologies suited to AI/ML environments.
- Provide technical expertise to overcome delivery challenges and drive overall success.
- Collaborate with data scientists, AI engineers, and architects to translate technical outputs into business-relevant outcomes.
Required Qualifications
Education
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Master's degree or MBA is an advantage.
Experience
- 5–8 years of technical management experience, with at least 3 years overseeing AI, data, or advanced analytics initiatives.
- Proven track record of delivering complex, multi-stakeholder technology projects on time and within budget.
- Experience with agile, hybrid, or waterfall methodologies in a technology or consulting environment.
- Prior client-facing or consulting experience is highly desirable.
Certifications
- PMP or equivalent – required.
- PMI-ACP, PRINCE2, or agile certifications – preferred.
- Cloud platform certifications (AWS, Azure, GCP, Databricks) – advantageous.
