Intern, Charging & Smart Energy - Summer 2026

Confirmed live in the last 24 hours

Lucid Motors

Newark, CA

On-site

Posted March 26, 2026

Job Description

Leading the future in luxury electric and mobility

At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.

We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.

Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

We are looking for a passionate and talented Computer Science Intern to help build a next-generation cloud platform that powers V1G (Vehicle-to-Grid) services. This platform is essential for enabling seamless communication between utilities, OEMs, and EV charging systems, driving smarter energy management and sustainable mobility.

Your contributions will directly impact the scalability, reliability, and performance of our core technology infrastructure. This is an excellent opportunity to gain hands-on experience in cloud-native development, DevOps principles, and large-scale system architecture within a fast-paced technology environment.

Key Responsibilities

· Platform Development & Integration: Build APIs, scripts, and secure authentication for V1G services and DERMS/OEM systems.

· Testing & Quality Assurance: Validate features through unit, integration, and end-to-end tests to ensure reliability and scalability.

· Automation & Monitoring: Configure monitoring tools (Prometheus, Grafana) and maintain operational visibility.

· Documentation & Collaboration: Create technical documentation and work closely with product managers and technical specialists on architecture

Required Skills & Qualifications

· Currently pursuing a degree in Computer Science, Software Engineering, or related field.

· Required: Python/Java/Node.js, REST APIs, cloud basics (AWS/Azure/GCP), Linux, problem-solving.

· Preferred: Docker/Kubernetes, CI/CD pipelines, Git, security standards, smart grid/V1G concepts.

· Knowledge of energy systems, IoT, or EV charging protocols (OCPP, ISO 15118) is a plus.

· Excellent problem-solving and communication skills.

Preferred Skills

· Experience with microservices architecture and containerization (Docker, Kubernetes).

· Exposure to data security and encryption standards.

· Interest in smart grid technologies and vehicle-to-grid (V2G/V1G) concepts.

· Familiarity with major cloud providers (AWS, Azure, GCP).

· Understanding of CI/CD pipelines and tools (Jenkins, GitLab CI, GitHub Actions).

· Experience with Git version control

What You’ll Gain

· Practical experience in energy-tech and EV ecosystem integration.

· Opportunity to work on cutting-edge projects in sustainable mobility.

· Mentorship from industry experts in charging infrastructure and energy management.

At Lucid, we don’t just welcome diversity - we celebrate it! Lucid Motors is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, national or ethnic origin, age, religion, disability, sexual orientation, gender, gender identity and expression, marital status, and any other characteristic protected under applicable State or Federal laws and regulations.

Compensation Range: The compensation range for this position is specific to the locations listed below and is the range Lucid reasonably and in good faith expects to pay for the position taking into account the wide variety of factors that are considered in making compensation decisions, including job-related knowledge; skillset; experience, education and train

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