AI Red Team Engineer
Impact: AI safety improvement through systematic vulnerability discovery before deployment
Systematically probe AI systems for vulnerabilities, failure modes, and harmful outputs. Design and execute red-teaming exercises that test AI safety, security, and reliability under adversarial conditions, and report findings to improve model safety.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 55% Team / 45% Solo
- Client facing
- Sometimes
- Impact visibility
- High
- Travel
- Minimal
- Schedule flexibility
- Flexible
- Remote work
- Mostly Remote
- Typical work hours
- 40 to 50 hours/week
- Stress level
- Moderate
At a glance
- Median salary
- $155,000
- Entry-level
- $110,000 - $135,000
- Senior
- $210,000+
- Growth by 2033
- 35% (much faster than average)
- Demand
- Growing Fast
- Freelance potential
- Low
- Salary growth potential
- High - 65 to 80% growth from entry to senior
- Typical student debt
- $20,000 - $60,000
Skills you'll use
Hard skills
- Prompt engineering
- Python
- LLM evaluation
- Adversarial testing
- Security testing
- Report writing
Soft skills
- Analytical thinking
- Creative problem-solving
- Attention to detail
- Ethical reasoning
- Communication
Technical complexity: Very High
How to get there
- Minimum education
- Bachelor's Degree
- Licensing
- No
- Years to mid-career
- 2 to 4 years
- Years to senior
- 5 to 8 years
- Career switching
- Moderate
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- ML Engineer > AI Red Team Engineer > Senior AI Red Team Engineer > Staff Safety Engineer > Head of AI Red Team
Future outlook
- Automation probability
- 15% low risk as creative adversarial thinking requires human ingenuity
- AI disruption risk
- Low
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 8.2/10
- Meaning
- 8.8/10
- Work-life balance
- 7.2/10
- Prestige
- 8/10
- Social perception
- High