Staff AI Engineer

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

Director, NOC Delivery & Automation

What You Will Be Doing

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.

You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.

Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development

Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures

Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval

Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems

Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability

Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)

Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines

Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues

Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

8+ years of software engineering experi