SQA and Test Infrastructure Development Engineer

Department: ADAS - HDW & SW Eng, ADAS & Autonomous Vehicles

Lucid Motors is seeking a SQA and Test Infrastructure Development Engineer to help build the next generation of test, automation, and validation systems that power our in‑vehicle compute platforms, embedded controllers, and advanced driver‑assistance technologies. You will play a key role in ensuring that Lucid’s software and hardware meet the highest standards of safety, reliability, and performance—supporting everything from firmware development to large‑scale automotive validation.

This role sits at the intersection of DevOps, embedded systems, and automotive test engineering, enabling fast, safe, and scalable development for the world’s most advanced electric vehicles.

What you’ll be doing

• Architect and maintain DevOps pipelines and test automation infrastructure optimized for automotive and embedded development workflows, including cross‑compilation, ECU flashing, and hardware‑in‑the‑loop (HIL) validation
• Build internal tools and services that streamline embedded software testing, firmware deployment, and continuous integration for safety‑critical systems
• Collaborate with Embedded Software, Vehicle Integration, and Test Engineering teams to design scalable test environments for Lucid’s in‑vehicle compute modules and real‑time embedded platforms
• Implement containerized and cloud‑native systems using Docker and Kubernetes to orchestrate distributed test execution across lab and cloud resources
• Integrate automotive‑specific workflows into CI/CD systems, including static analysis, MISRA compliance, traceability, and automated regression testing
• Develop monitoring, logging, and diagnostic tools to ensure high availability and performance of embedded test infrastructure
• Support and extend test frameworks used for ECU validation, vehicle‑level testing, and manufacturing test

What we need to see

• BS/MS in Computer Science, Electrical Engineering, Computer Engineering, or related field
• 3+ years of experience in DevOps, embedded test infrastructure, or automation tooling
• Strong proficiency in Python and experience with frameworks such as Flask or Django
• Experience with embedded Linux, cross‑compilation, and deploying applications to embedded targets
• Familiarity with automotive communication protocols such as CAN bus, or Automotive Ethernet
• Experience with HIL/SIL systems, embedded test benches, or automotive validation environments such as vector Tools
• Proficiency with version control systems such as GIT or GitLab
• Strong Linux knowledge—deployment, debugging, system monitoring, and automation
• Familiarity with bash scripting and Linux‑based automation workflows

Ways to stand out from the crowd

• Background in deploying or maintaining embedded test automation systems, including HIL rigs or ECU validation setups
• Experience with real‑time operating systems (RTOS) or embedded firmware development
• Exposure to manufacturing test environments for automotive ECUs, embedded boards, or in‑vehicle compute modules
• Familiarity with cloud platforms (AWS, Azure, GCP) and infrastructure‑as‑code tools such as Terraform or Ansible
• Passion for building robust CI/CD pipelines and developer‑facing infrastructure for embedded systems

Bonus Qualifications – Agentic AI Tools & Intelligent Automation

Lucid is increasingly leveraging agentic AI systems to accelerate development, automate complex workflows, and enhance test intelligence. Experience with any of the following is a strong plus:

• Building or integrating AI‑driven DevOps agents for automated debugging, test generation, or pipeline optimization
• Experience with LLM‑powered tools for code analysis, anomaly detection, or automated documentation
• Familiarity with AI‑assisted test case generation, including reinforcement‑learning‑based or model‑based testing
• Experience using or developing autonomous agents that interact with CI/CD systems, embedded hardware, or cloud infrastructure
• Knowledge of AI‑driven observability platforms for predictive monitoring, log intelligence, or automated root‑cause analysis
• Understanding of agent orchestration frameworks such as LangChain, LangGraph, or similar tools
• Experience integrating AI agents with automotive workflows such as ECU flashing, HIL orchestration, or embedded diagnostics