AI / Emerging Tech Security Analyst

Alignerr Corp.; Mumbai; Remote; INR 2,066,000 - 3,444,000; Full time

Job summary

Alignerr is seeking AI Security Analysts to stress-test frontier AI models, identify vulnerabilities, and ensure safe, reliable operation. This is a fully remote hourly contract with a commitment of 10–40 hours per week, suitable for security professionals curious about AI.

You will analyze real-world AI and LLM security scenarios, review cases like prompt injection and data leakage, and apply threat modeling to emerging AI tech. Work independently and communicate findings in writing.

Qualifications

• Background in cybersecurity or information security.
• Solid understanding of threat modeling applied to AI systems.
• Analytical and precise when evaluating complex systems and attack surfaces.

Responsibilities

• Analyze real-world AI and LLM security scenarios under adversarial conditions.
• Review cases involving prompt injection, data leakage, model abuse, jailbreaking, and system misuse.
• Classify security issues by impact and likelihood; recommend mitigations.
• Apply threat modeling frameworks to emerging AI technologies and deployments.
• Help evaluate and improve AI system behavior to stay safe, aligned, and resilient.
• Work independently on task-based assignments at your own pace.

Skills

Cybersecurity

Threat Modeling

AI Security

Analytical Thinking

Independent Work

Education

Cybersecurity background

Tools

MITRE ATT&CK

OWASP

Penetration Testing

Job description

About The Role

What if your security expertise could directly shape how the world's most powerful AI systems defend themselves against misuse, manipulation, and attack? We're looking for AI Security Analysts to stress-test frontier models — probing their boundaries, identifying vulnerabilities, and helping ensure that cutting-edge AI remains safe, reliable, and resistant to adversarial exploitation.

This is a fully remote, flexible contract role built for security professionals who are curious about AI and want to work at the intersection of two of the most consequential fields in tech.

• Organization: Alignerr


• Type: Hourly Contract


• Location: Remote


• Commitment: 10–40 hours/week

What You’ll Do

• Analyze real-world 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, jailbreaking, and system misuse


• Classify security issues by real-world impact and likelihood, and recommend appropriate mitigations


• Apply threat modeling frameworks to emerging AI technologies and deployment contexts


• Help evaluate and improve AI system behavior so it stays safe, aligned, and resilient against exploitation


• Work independently on task-based assignments at your own pace

Who You Are

• Background in cybersecurity, information security, or a closely related field


• Solid understanding of modern threat modeling — and a genuine interest in how it applies to AI systems


• Analytical and precise when evaluating complex systems and potential attack surfaces


• Curious about how AI models are built, deployed, and potentially abused


• Comfortable working independently and communicating findings clearly in writing

Nice to Have

• Hands-on experience with penetration testing, red teaming, or vulnerability research


• Familiarity with large language models, prompt engineering, or AI safety concepts


• Background in application security, API security, or cloud security


• Experience with security frameworks such as MITRE ATT&CK or OWASP


• Prior involvement in bug bounty programs or responsible disclosure

Why Join Us

• Work directly on frontier AI systems alongside leading AI research labs


• Fully remote and flexible — work when and where it suits you


• Freelance autonomy with the structure of meaningful, impactful work


• Contribute to AI safety at a critical moment in the development of the technology


• Potential for ongoing work and contract extension as new projects launch