Delivery Lead – AI Data Projects

Accountabilities

• Own end-to-end project delivery: Take accountability for a portfolio of AI data projects, ensuring data quality, delivery timelines, client satisfaction, unit economics, and gross margin targets are consistently achieved.

• Lead cross-functional teams: Coordinate project managers, engineers, researchers, data scientists, supply managers, product teams, and other specialists to maintain alignment and deliver successful outcomes.

• Manage project execution: Oversee project discovery, scope definition, planning, implementation, resource allocation, and adoption. Step in directly as a hands-on project manager when needed.

• Drive operational excellence: Establish and maintain effective delivery processes, communication practices, reporting standards, project status updates, retrospectives, and execution frameworks.

• Manage risks and resolve issues: Identify potential delivery challenges early, implement mitigation plans, remove blockers, and ensure stakeholders have clear visibility into progress and risks.

• Build strong client relationships: Serve as a trusted partner to clients and technical stakeholders, manage expectations, communicate progress transparently, and resolve issues to support satisfaction and long-term retention.

• Support business development: Collaborate with commercial teams to scope new opportunities, shape project proposals, define viable delivery models, and transition prospects into successful engagements.

• Optimize commercial performance: Balance delivery quality and customer outcomes with operational efficiency, resource utilization, unit economics, and profitability.

• Improve team performance: Motivate and support delivery teams, identify opportunities to improve workflows, and develop repeatable practices that enhance quality, speed, and consistency.

• Lead continuous improvement initiatives: Introduce new tools, processes, and working methods across the delivery organization, gather feedback, measure impact, and refine approaches based on results.

Requirements

• Relevant AI experience: Demonstrated experience working in the AI sector, particularly in startup environments, with responsibility for clients, teams, or projects at scale.

• Complex project management: Proven ability to manage complex projects from discovery and decomposition through scope planning, implementation, and adoption.

• Client-facing leadership: Significant experience managing client relationships and complex engagements. A consulting background at Engagement Manager, Associate Partner, or a comparable level is particularly relevant.

• AI and GenAI knowledge: Strong understanding of artificial intelligence and generative AI technologies, market trends, and practical applications.

• Technical foundation: Basic knowledge of statistics, machine learning, data science, and data generation, with the ability to collaborate effectively with technical specialists.

• Educational background: A bachelor's or master's degree in a STEM discipline, such as computer science, mathematics, or physics.

• Leadership and coordination: Ability to lead distributed, multidisciplinary teams, align stakeholders around shared objectives, and maintain accountability across complex delivery environments.

• Client communication: Excellent communication and relationship-management skills, including the ability to explain technical concepts, manage expectations, and navigate challenging conversations.

• Operational and commercial judgment: Strong organizational skills and the ability to balance quality, deadlines, resources, and financial performance.

• Problem-solving and adaptability: A proactive approach to resolving issues, managing ambiguity, and adapting plans as client needs and project requirements evolve.

• Continuous improvement mindset: Motivation to refine delivery processes, introduce effective working methods, and use data and feedback to improve performance.

Benefits

• Competitive compensation: A competitive compensation package; the specific salary range is not provided in the job description.

• Flexible remote work: A fully remote working arrangement with a flexible schedule.

• International environment: Opportunity to collaborate with a globally distributed team of AI specialists and professionals across multiple disciplines.

• Leading-edge technology: Exposure to advanced AI and generative AI projects that contribute to the development and evaluation of next-generation models.

• High-profile client projects: Opportunity to work with leading organizations in the AI industry, including major technology companies, established enterprises, and innovative AI startups.

• Professional growth: Opportunities to deepen expertise in AI delivery, client management, cross-functional leadership, and operational strategy.

• Meaningful impact: The chance to help shape AI innovation by ensuring complex data projects are delivered efficiently, reliably, and to high quality standards.

• Additional benefits: Healthcare coverage, paid leave, pension arrangements, equity, and other location-specific benefits are not specified in the provided job description and should be confirmed with the hiring team.