AI Deployment Strategist

Key Responsibilities 1. Strategic Project Leadership - Drive end-to-end delivery of AI transformation initiatives, from discovery and business case development to deployment and value realization. - Define measurable success metrics (e.g., ROI, operational efficiency improvements, and automation rates) and ensure accountability for outcomes. - Translate enterprise business objectives into structured execution roadmaps aligned with organizational growth strategies. - Prioritize initiatives based on commercial impact, feasibility, and strategic alignment. 2. Business & Solution Strategy - Identify operational challenges across procurement, inventory, manufacturing, and logistics. - Develop AI deployment strategies that balance technical feasibility with business value. - Create phased implementation plans (MVP, pilot, and full-scale deployment) with clearly defined milestones. - Support executive-level discussions by presenting solution frameworks, cost-benefit analyses, and digital transformation roadmaps. 3. Cross-Functional Execution Management - Lead cross-functional teams, including AI, Platform, Systems, Performance Engineering, and Operations, to deliver projects successfully. - Implement Agile or hybrid project management methodologies for enterprise AI deployments. - Manage project scope, dependencies, technical risks, change management, and stakeholder alignment. - Ensure all project deliverables comply with security, governance, and enterprise standards. 4. Startup Scaling & Operational Excellence - Develop standardized deployment playbooks and repeatable delivery frameworks. - Enhance internal project management processes, reporting practices, and risk management. - Contribute to product strategy discussions and deployment architecture planning. - Strengthen feedback loops between client implementations and the product development roadmap. 5. Commercial & Stakeholder Management - Serve as a strategic advisor to enterprise and public-sector clients. - Support pre-sales activities, including solution scoping, proposal preparation, and technical-commercial alignment. - Manage client expectations at both operational and executive levels. - Identify opportunities for account growth and expansion through performance insights and optimization outcomes. Requirements Experience: - 2–5 years of professional experience in project management, product management, business consulting, or technology delivery. - Prior hands-on experience in engineering, software development, or technical operations is preferred. - Experience working on AI, data platforms, analytics, or digital transformation projects is strongly preferred. - Prior experience in startups, technology companies, consulting firms, or enterprise environments is an advantage. Language Skills: - Professional working proficiency in English. Technical & Business Acumen: - Strong interest in AI, generative AI, large language models (LLMs), and AI-driven products. - Ability to communicate effectively with both technical and non-technical stakeholders. - Familiarity with Agile, Scrum, or hybrid project management methodologies. - Understanding of enterprise business processes, governance, and stakeholder management. Education: - Bachelor's degree in Business, Management, Economics, Engineering, Computer Science, or a related field. - A background in AI, data science, or machine learning is a plus but not mandatory. - Project Management Professional (PMP) certification is a plus but not mandatory. Desired Skills: - Experience working with enterprises or government-linked organizations. - Exposure to AI product launches or go-to-market initiatives. - Prior experience in consulting, investment, or strategy.