Job Description

The role

As Head of Data & AI you will own Driivz's data platform and AI product layer end to end. You will report directly to the TBD and work closely with global commercial and customer success leadership. You are not a functional manager overseeing an analytics team. You are the technical and product owner of a new business line, responsible for both what gets built and what gets sold.

The work spans the full stack: data infrastructure, machine learning, applied AI, and the commercial product layer that sits on top. The problems are genuinely hard -- multi-vendor hardware, real-time event streams at scale, complex energy market signals, and operators running critical public infrastructure that cannot tolerate errors.

What you will own

• Data platform architecture and delivery -- the foundation that everything else depends on
• Machine learning and AI system design, from model training through to production operation
• Real-time data ingestion and processing at scale across heterogeneous hardware and markets
• All foundational technology decisions: stack, tooling, infrastructure approach
• Production reliability of every system and model the team ships
• AI product scope and packaging
• Technical relationships with Driivz's most strategically important operator accounts
• Data strategy and technology roadmap
• teamwork with the CPO to define the art of the possible use cases

Requirements

What we are looking for

• You have built a data or AI platform from 0 to 1 at a B2B SaaS or industrial technology company.
• You have shipped AI systems that execute decisions or actions in production.
• You have led a data or AI team across engineering and science disciplines.
• You are technically deep and commercially aware. You can design a data architecture in the morning and have a credible commercial conversation with a senior operator in the afternoon.
• You operate well under ambiguity. You are the person who turns the former into the latter.

Strong signal

• EV, energy, smart grid, or industrial IoT background or a clear track record of acquiring deep domain knowledge quickly in a new technical vertical
• Production experience with agentic or autonomous AI including cost optimization and efficiency
• Industrial or IoT protocol experience: OCPP, MQTT, or equivalent, high-frequency event streams from hardware at scale
• Snowflake at production scale: schema design, real-time ingestion pipelines, ML integration, cost governance
• Confidence calibration and threshold design for AI systems that operate without human approval on every decision
• Effective cross-timezone leadership: comfortable building a high-performing team while operating as a daily peer to global commercial and CS leadership