Director, Data Platform & AI

Confirmed live in the last 24 hours

ChargePoint

Bangalore, India

On-site

Posted March 20, 2026

Job Description

About Us

With electric vehicles expected to be nearly 30% of new vehicle sales by 2025 and more than 50% by 2040, electric mobility is becoming a reality. ChargePoint (NYSE: CHPT) is at the center of this revolution, powering one of the world’s leading EV charging networks and a comprehensive set of hardware, software and mobile solutions for every charging need across North America and Europe. We bring together drivers, businesses, automakers, policymakers, utilities and other stakeholders to make e-mobility a global reality.

Since our founding in 2007, ChargePoint has focused solely on making the transition to electric easy for businesses, fleets and drivers. ChargePoint offers a once-in-a-lifetime opportunity to create an all-electric future and a trillion-dollar market.

At ChargePoint, we foster a positive and productive work environment by committing to live our values of Be Courageous, Charge Together, Love our Customers, Operate with Openness, and Relentlessly Pursue Awesome. These values guide how we show up every day, align, and work together to build a brighter future for all of us.

Join the team that is building the EV charging industry and make your mark on how people and goods will get everywhere they need to go, in any context, for generations to come.

Reports To

VP, Engineering

Role Overview

As the Director, Data Platform & AI, you will set the vision and strategy for ChargePoint’s data and AI platforms, and lead multi‑disciplinary teams (Data Engineering, Analytics, Classical ML/Data Science, and Gen/Agentic AI) to deliver innovative, customer‑centric data and AI features at global scale. You will partner closely with Product, Software, Hardware, Cloud/SRE, Security, and Business stakeholders to translate data product and feature requirements into roadmaps, architectures, and outcomes that accelerate ChargePoint’s transformation into an AI‑first company.

What You Will Be Doing

Vision & Strategy: Define a 2–3 year Data & AI platform vision and investment plan that aligns with ChargePoint’s product portfolio and growth goals; articulate north‑star outcomes, KPIs, and staged milestones for platform, products, and teams.
Product Ideation & Roadmapping: Work with Product Management to ideate AI‑powered features (e.g., intelligent pricing and load management, driver experience personalization, fleet insights, predictive maintenance, customer support automation), shape PRDs, and prioritize a balanced roadmap across foundational platform work and near‑term product impact.
Platform Architecture: Own end‑to‑end architecture for the data platform (ingestion, storage, transformation, governance, serving, observability) and AI stack (feature stores, model registry, evaluation, MLOps, prompt/policy libraries, RAG infrastructure, agent orchestration, guardrails).
Execution Leadership: Lead multiple squads to deliver reliable, secure, cost‑efficient data services and AI capabilities; establish engineering excellence (design reviews, architecture standards, SLAs/SLOs, incident playbooks, cost and performance baselines).
Gen AI & Agentic AI: Drive applied use cases of LLMs and agent frameworks (retrieval‑augmented generation, tool‑using agents, workflow automation) with measurable impact; set patterns for prompt engineering, safety, evaluation, and human‑in‑the‑loop controls.
Mentorship & Talent Development: Build, coach, and mentor talent across Data Engineering, Analytics, ML/DS, and GenAI; grow emerging leaders; foster a culture of curiosity, accountability, and continuous learning.
Cross‑Functional Partnering: Proactively connect with engineering leaders across software, cloud, security, and QA to align designs and delivery; remove blockers and ensure seamless integration of data and AI features in customer experiences.
Data Governance & Compliance: Champion data quality, lineage, cataloging, privacy/security, and responsible AI practices (model documentation, bias/effectiveness monitoring, PII handling, policy compliance).
Operational Excellence: Implement robust MLOps