Offensive AI Security Engineer – Red Team

Lucid Motors; Newark (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Lucid Motors is seeking an Offensive AI Security Engineer to join their AI Red Team. This role focuses on adversarial machine learning and offensive security strategies for AI systems, aiming to uncover vulnerabilities in automotive security. The successful candidate will work on innovative tools and automation to enhance security measures in vehicle AI applications, contributing to the future of luxury electric vehicles.

Benefits

medical insurance

dental insurance

vision insurance

401k

vacation time

equity program eligibility

Qualifications

• Hands-on experience with AI/ML exploitation and adversarial ML.
• Strong background in attacking AI models, including deep learning systems.
• Proficiency in Python, C, C++ for AI security research.

Responsibilities

• Design and execute adversarial attacks on AI-powered security systems.
• Conduct LLM-based penetration testing for AI security flaws.
• Develop AI-enhanced security automation tools.

Skills

AI/ML exploitation

adversarial ML

penetration testing

red teaming AI models

Education

Bachelor’s degree in Cybersecurity or related field

Tools

TensorFlow

PyTorch

Hugging Face

OpenAI APIs

LangChain

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.

Job Title:Offensive AI Security Engineer – Red Team

We are seeking anOffensive AI Security Engineerto join ourAI Red Team within theSecurity Engineering team . This role focuses onadversarial machine learning (ML), AI-driven offensive security, and red team ing AI systemsto uncover vulnerabilities inAI-powe red automotive security models and vehicle platforms.

As part ofLucid’s Offensive AI Security team , you willattack, manipulate, and exploit AI/ML modelsto identifyreal-world threats and weaknesses in AI-driven security solutions. You will developAI-enhanced security automation tools, performLLM-based penetration testing, and integrateAI/ML attack techniques into offensive security operations.

Key Responsibilities:

• Design and executeadversarial attacksonAI-powe red security systems.
• ConductLLM-based penetration testingto uncoverAI security flaws in vehicle cybersecurity applications.
• Identifyattack surfaces in AI-driven perception systems(LiDAR, Radar, Cameras) and develop exploits againstautomotive AI models.

AI-Driven Offensive Security Automation

• Build tools and systemsto analyzeemerging AI threatsinvehicle security and enterprise AI models.
• DevelopAI-assisted security automation toolsfor:
• Reconnaissance– Automate vulnerability discovery usingLLMs and RAG-based intelligence gathering.
• Exploitation– UseAI to generate attack payloads and automate offensive security operations.
• Fuzzing– Enhanceautomated fuzz testing with AI-driven input mutation strategies.
• Reverse Engineering– ApplyLLM-assisted binary analysisfor rapid security assessments.
• Buildoffensive and defensive AI security tools, integrating ML-driven automation intosecurity assessments and exploit development.

ML-Driven Security Research & Exploitation

• Use ML to characterize a program, identifying security-critical functions and behavioral anomalies.
• UnderstandLLVM Intermediate Representation (LLVM IR)to analyzecompiled AI/ML softwarefor security weaknesses.
• Threat Detection– Use ML to automate malware detection and anomaly recognition.
• Cryptographic Algorithm Classification– Identify cryptographic weaknesses in compiled binaries.
• Function Recognition– Use AI models toautomate binary function analysis and decompilation.
• Vulnerability Discovery– Automatezero-day discoveryusing ML-based exploit p red iction models.
• EvaluateML security models for robustness, performance, and adversarial resilience.

Offensive AI Research & Red Team ing Strategy

• Researchnovel AI attack techniquesand evaluate theirimpact on vehicle cybersecurity and enterprise AI security models.
• Collaborate withinternal Red Team s, SOC analysts, and AI security researchersto refineAI-driven offensive security approaches.
• Stay ahead ofemerging AI threats, tracking advancements inAI security, adversarial ML, and autonomous vehicle AI exploitation.

Requi red Skills & Qualifications:

AI Red Team ing & Offensive Security Expertise

Hands-on experience withAI/ML exploitation, adversarial ML, and AI-driven pentesting.

Strong background inattacking AI models, includingLLMs, deep learning systems, and computer vision AI.

Experience withLLM-based vulnerability analysis, prompt engineering attacks, and model evasion techniques.

Proficiency inpenetration testing, AI fuzzing, and red team ing AI-driven security applications.

Cybersecurity & AI Security Research

Experience inexploiting AI-powe red vehicle security mechanisms.

Ability toanalyze, test, and exploit AI models within embedded systems and cloud environments.

Programming & Security Tooling

StrongPython, C, C++skills forAI security research and offensive security automation.

Proficiency withAI security frameworks(TensorFlow, PyTorch, Hugging Face, OpenAI APIs, LangChain).

Hands-on experience withreverse engineering tools(Ghidra, IDA Pro, Binary Ninja, Qiling, Angr).

Familiarity withAI fuzzing tools (AFL++, Honggfuzz, Syzkaller) and adversarial ML frameworks (CleverHans, Foolbox, ART).

Prefer red Qualifications:

• Bachelor’s degree in Cybersecurity, AI/ML, Computer Science, or related technical field(s) is required. Master’s degree or higher education is preferred.
• Experience inoffensive AI security, red team ing AI models, or AI-powe red security automation.
• Prior work inLLM-based security analysis, AI-driven pentesting, and adversarial ML research.

Salary 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 training; certifications; and other relevant business and organizational factors.

Additional Compensation and Benefits: Lucid offers a wide range of competitive benefits, including medical, dental, vision, life insurance, disability insurance, vacation, and 401k. The successful candidate may also be eligible to participate in Lucid’s equity program and/or a discretionary annual incentive program, subject to the rules governing such programs. (Cash or equity incentive awards, if any, will depend on various factors, including, without limitation, individual and company performance.)

To all recruitment agencies: Lucid Motors does not accept agency resumes. Please do not forward resumes to our careers alias or other Lucid Motors employees. Lucid Motors is not responsible for any fees related to unsolicited resumes.

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