AI Red Teamer, LLM Generalist

About Handshake
Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.

Why join Handshake now:

Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel

Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions

Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders

Build a massive, fast-growing business with billions in revenue

About Handshake AI

Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.

About the Role
As an AI Red Teamer, you will stress-test large language models by intentionally trying to break them. Rather than checking whether an answer is correct, you will design creative, adversarial prompts that expose vulnerabilities: unsafe content, bias, broken guardrails, hallucinations, prompt injection weaknesses, and unexpected behaviors. Your work directly supports AI safety and model robustness for leading research labs.

This is a generalist red teaming role. You will probe models across the full spectrum of risk categories, including content safety, CBRN (chemical, biological, radiological, nuclear), cybersecurity, persuasion and influence operations, child safety, self-harm, over-companionship, and regulatory compliance. Red teaming may span text, image, voice, and agentic model capabilities depending on project needs.

This role requires creativity, curiosity, and an ability to think like an adversary while operating with strong ethical judgment.

Craft creative prompts and multi-turn scenarios to stress-test AI guardrails across diverse risk categories

Discover ways around safety filters, restrictions, and defenses using jailbreak, evasion, and prompt injection techniques

Explore edge cases to provoke disallowed, harmful, or incorrect outputs

Evaluate and score model responses against structured harm taxonomies and severity rubrics

Document experiments clearly, including what you tried, why you tried it, and what it revealed

Review and refine adversarial prompts generated by other team members

Contribute to harm taxonomy development, calibration exercises, and inter-rater reliability work

Collaborate with engineers, data scientists, and researchers to share findings and strengthen defenses

Work with potentially disturbing content on a regular basis (see Content Warning below)

Stay current on jailbreaks, attack methods, and evolving model behaviors

 
Desired Capabilities

Strong hands-on experience using multiple LLMs (ChatGPT, Claude, Gemini, open-source models, etc.)

Intuition for crafting adversarial prompts; familiarity with jailbreak or evasion techniques is a strong plus

Creative, adversarial problem-solving skills

Clear and thoughtful written communication

Strong ethical judgment and the ability to separate adversarial thinking from personal values

Self-directed, collaborative, and comfortable in feedback-heavy environments

Curiosity, persistence, and comfort with frequent failure in experimentation

 
Extra Credit

Familiarity with Python or other scr…