AI / Emerging Tech Security Analyst
Alignerr · Spain
- Hybrid
- Contract
- $80,000 / year
- Spain
Job highlights
- Analyze AI/LLM security for vulnerabilities.
- Evaluate prompt injection and model abuse.
- Classify issues and recommend mitigations.
- Apply threat modeling to AI technologies.
- Work remotely on your own schedule.
About the role
About The Role
What if your security expertise could directly shape how the world's most advanced AI systems defend themselves against attack? We're looking for AI Security Analysts to probe frontier models, uncover vulnerabilities, and help ensure that cutting-edge AI remains safe, reliable, and resistant to misuse. This is a fully remote, flexible contract role for security professionals who are curious about how modern AI systems can be exploited — and how to stop it. You'll work directly with realistic adversarial scenarios drawn from the frontier of AI development.
Organization
Alignerr
Type
Hourly Contract
Location
Remote
Commitment
10–40 hours/week
What You'll Do
- Analyze AI and LLM security scenarios to understand how models behave under adversarial or unexpected conditions
- Review and evaluate cases involving prompt injection, data leakage, model abuse, and system misuse
- Classify security issues and recommend appropriate mitigations based on real-world impact and likelihood
- Apply threat modeling frameworks to emerging AI technologies and deployment contexts
- Help evaluate and improve AI system behavior to keep it safe, aligned, and resistant to exploitation
- Work independently and asynchronously on task-based assignments — fully on your own schedule
Who You Are
- Background in cybersecurity, information security, or a closely related field
- Strong understanding of security threat modeling applied to software systems — bonus points if you've thought deeply about AI-specific attack surfaces
- Analytically sharp and precise — you notice edge cases, think adversarially, and document findings clearly
- Genuinely curious about how large language models and AI systems are built, deployed, and potentially exploited
- Self-motivated and comfortable working independently without hand-holding
Nice to Have
- Hands-on experience with penetration testing, red teaming, or vulnerability research
- Familiarity with LLM concepts — prompt engineering, fine-tuning, RLHF, or model deployment pipelines
- Background in applied cryptography, access control, or secure systems design
- Experience with AI safety, alignment research, or responsible AI practices
- Prior work in bug bounty programs or adversarial ML research
Why Join Us
- Work directly on frontier AI systems alongside leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact work
- Contribute to AI safety at a moment when it matters most
- Potential for ongoing work and contract extension as new projects launch
Key skills/competency
- AI Security Analysis
- LLM Security
- Cybersecurity
- Threat Modeling
- Vulnerability Research
- Adversarial ML
- Prompt Injection
- Data Leakage
- System Misuse
- AI Safety
Skills & topics
- AI Security Analyst
- Cybersecurity
- AI
- LLM
- Threat Modeling
- Vulnerability Research
- Remote
- Contract
- Prompt Injection
- AI Safety
How to get hired
- Tailor your resume: Highlight cybersecurity, threat modeling, and AI/LLM security experience.
- Showcase analytical skills: Provide examples of identifying edge cases and documenting findings clearly.
- Demonstrate self-motivation: Emphasize your ability to work independently and asynchronously.
- Address AI curiosity: Express genuine interest in AI system exploitation and safety.
- Prepare for technical discussion: Be ready to discuss adversarial scenarios and AI attack surfaces.
Technical preparation
Study AI/LLM attack vectors.,Practice threat modeling frameworks.,Review prompt injection techniques.,Familiarize with ML security tools.
Behavioral questions
Describe a complex security problem.,How do you handle ambiguity?,Showcase your analytical thinking.,Explain your interest in AI safety.
Frequently asked questions
- What is the primary focus of the AI Security Analyst role at Alignerr?
- The AI Security Analyst role at Alignerr focuses on probing frontier AI and LLM models to uncover vulnerabilities, evaluate security risks like prompt injection and data leakage, and recommend mitigations to ensure AI systems are safe and resistant to misuse. You'll work with realistic adversarial scenarios from AI development.
- Is this a full-time or part-time position, and what is the work arrangement?
- This is an hourly contract role at Alignerr, offering a flexible commitment of 10-40 hours per week. It is a fully remote position, allowing you to work when and where it suits you. This offers freelance autonomy with meaningful, high-impact work on cutting-edge AI systems.
- What specific cybersecurity skills are most important for the AI Security Analyst role?
- Key skills for the AI Security Analyst role at Alignerr include a strong background in cybersecurity or information security, with a deep understanding of security threat modeling as applied to software systems. Experience with AI-specific attack surfaces, penetration testing, red teaming, or vulnerability research is highly valued. Familiarity with LLM concepts and AI safety practices is also beneficial.
- How does Alignerr ensure AI systems remain safe and resistant to exploitation in this role?
- Alignerr ensures AI systems remain safe through the work of AI Security Analysts who analyze security scenarios, evaluate potential misuse, classify issues, and recommend mitigations. They apply threat modeling frameworks and help improve AI system behavior to keep it aligned and resistant to exploitation, contributing to critical AI safety research.
- What kind of projects can an AI Security Analyst expect to work on at Alignerr?
- As an AI Security Analyst at Alignerr, you can expect to work on task-based assignments involving realistic adversarial scenarios drawn from the frontier of AI development. This includes analyzing LLM security, evaluating prompt injection, data leakage, model abuse, and applying threat modeling to emerging AI technologies, directly contributing to the safety of advanced AI systems.