Senior 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.

ChargePoint is looking for a Senior GenAI Engineer who will lead the design, development, and operation of production‑grade Generative AI systems. You will architect and deliver LLM‑powered applications, including Copilot‑style experiences, AI agents, and automation at enterprise scale.

You will operate with high autonomy, own complex technical initiatives end‑to‑end, and influence GenAI architecture and standards across teams.

Reports To

Senior Manager-Information Security

What You Will Be Doing

As a Senior GenAI Engineer, you will:

• Architect and build LLM‑based applications such as copilots, chatbots, and AI agents


• Design and optimize RAG and grounded AI systems using enterprise data


• Lead development of agentic workflows with tool/function calling and multi‑step reasoning


• Own backend services and APIs for AI inference and orchestration


• Drive LLMOps / GenAIOps practices (evaluation, monitoring, CI/CD, versioning)


• Optimize AI systems for quality, cost, latency, and reliability


• Apply and advocate for Responsible AI and security‑by‑design


• Mentor engineers and influence AI engineering best practices


• Partner with product, platform, and security teams to shape AI strategy

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


• Ability to balance speed, quality, and risk in production AI deployments


• Passion for building scalable, maintainable, and responsible AI platforms


• Strong communication skills with engineers, product managers, and leadership

Requirements

• 10+ years of professional software engineering experience


• Strong development skills in Python; experience with Java, FastAPI, Django, and modern backend frameworks for AI service development


• Extensive hands-on experience with LLMs and generative AI systems


• Strong experience with RAG, embeddings, Elasticsearch including vector and hybrid search, and prompt engineering


• Experience building Copilot-style, conversational, and agent-based AI systems


• Strong understanding of distributed systems, APIs, microservices architecture, and event-driven patterns


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


• Familiarity with LLMOps and MLOps practices

Good to Have

• Experience with AI governance, compliance, or regulated enterprise environments


• Experience with vector databases and retrieval optimization


• Prior ownership of AI systems running in production at scale

Location

Remote location in India

We are committed to an inclusive and diverse team. ChargePoint is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status. 

If there is a match between your experiences/skills and the Company needs, we will contact you directly.