AI Red Team Engineer - English
Role details
Job location
Tech stack
Job description
- Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent
- Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing
- 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation
- Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review
LILT in the News
- Featured in The Software Report's Top 100 Software Companies!
- LILT makes it onto the Inc. 5000 List.
- LILT's continues to be an intellectual powerhouse, holding numerous patents that help power the most efficient and sophisticated AI and language models in the industry.
- Check out all our news on our website.
Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy.
At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com.
Requirements
- Deep Understanding of Generative AI and main models, including their underlying architectures, training processes, and potential failure modes. This includes knowledge of concepts like prompt engineering, fine-tuning, and reinforcement learning with human feedback (RLHF)
- Cybersecurity & Threat Modeling: Experience in cybersecurity principles, including threat modeling, vulnerability assessment, and penetration testing. Ability to identify attack vectors, simulate real-world threats, and understand the potential impact of an attack.
- Data Analysis & NLP: Strong analytical skills to dissect model outputs, identify subtle biases or factual errors, and recognize patterns in how the model responds to different inputs. A background in Natural Language Processing (NLP) would be highly beneficial.
- Ethical Hacking Mindset: A commitment to using her/his skills for defensive and security-focused purposes, adhering to a strict ethical code, and understanding the importance of responsible disclosure.
Core Requirements
- You hold a Bachelor's or Master's Degree in Computer Science, Software Engineering, Cybersecurity, Digital Forensics or other related fields.
- Your level of English is advanced (C1) or above
- Adversarial thinking
- Knowledge of vulnerabilities, common model vulnerabilities (prompt injection, prompt-history leakage, data exfiltration via RAG).
- Experience in AI/ML security, evaluation, and red teaming, particularly with LLMs, AI agents, and RAG pipelines.
- You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.
- Proficient in scripting and automation using Python, Bash, or PowerShell.
- Familiar with AI red-teaming frameworks such as garak or PyRIT.
Preferred Requirements
- Physical-world adversarial testing
- Experienced with containerization and CI/CD security tools, especially Docker.
- Proficient in offensive exploitation and exploit development.
- Skilled in reverse engineering using tools like Ghidra or equivalents.
- Expertise in network and application security, including web application security.
- Knowledge of operating system security concepts such as Linux privilege escalation and Windows internals.
- Familiar with secure coding practices for full-stack development.
Benefits & conditions
- Get paid for your expertise, with rates that can go up to $55/hour depending on your skills, experience, and project needs.
- Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.
- Work on advanced AI projects and gain valuable experience that enhances your portfolio.
- Influence how future AI models understand and communicate in your field of expertise.