Vice President, Data & AI Engineering

Powerfleet is a global provider of AIoT software-as-a-service solutions for the mobile asset industry. The Vice President, Data & AI Engineering will lead the strategy, architecture, and execution of enterprise data and AI capabilities, including data engineering, AI/ML, GenAI, AI platforms, and intelligent automation. This role will build scalable, secure, production-ready solutions and lead a global engineering organization while partnering with executive and cross-functional stakeholders.

Responsibilities:

• Define and execute Powerfleet’s Data & AI engineering strategy, roadmap, and priorities in alignment with business and product objectives
• Establish scalable, secure, and cost-effective architectures for enterprise data, AI/ML, GenAI, and AI-enabled applications
• Build a strong data foundation that supports analytics, machine learning, real-time intelligence, and AI use cases, promoting common platforms, reusable services, APIs, and engineering practices while enabling teams to innovate
• Advise executive leadership on emerging AI capabilities, opportunities, risks, and technology investments
• Lead the development and adoption of capabilities across AI/ML, GenAI, AI agents, intelligent automation, and related technologies and establish practical frameworks and platforms that enable teams to move AI solutions from experimentation into production
• Advance MLOps/LLMOps, model evaluation, observability, governance, and other capabilities needed to operate AI reliably at scale
• Build and lead a high-performing global Data & AI engineering organization across relevant disciplines and geographies
• Partner with Security, Legal, Privacy, Risk, and other stakeholders to establish appropriate AI governance and responsible AI practices
• Establish appropriate metrics for platform adoption, engineering productivity, reliability, cost efficiency, and AI impact and manage technology investments, strategic vendors, and build-versus-buy decisions within the Data & AI domain
• Communicate strategy, progress, opportunities, and risks effectively to executive leadership and key stakeholders

Requirements:

• 15+ years of experience in technology or engineering, with significant experience across data, software, cloud, platform, or AI engineering
• 7+ years of leadership experience building and leading engineering teams, preferably in global or distributed organizations
• Experience developing enterprise data and AI platforms, architectures, and engineering strategies
• Strong understanding of modern data platforms, cloud technologies, data engineering, distributed systems, AI/ML, and software engineering
• Familiarity with modern GenAI patterns such as LLMs, RAG, agents, orchestration, evaluation, and AI observability
• Strong executive communication and the ability to work effectively with both technical and non-technical stakeholders
• Bachelor's degree in computer science, Engineering, Data Science, or a related field; advanced degree preferred
• advanced degree preferred