AI Safety Engineer
Impact: Prevention of AI-caused harm and building public trust in AI systems
Build technical systems and processes that ensure AI models behave safely, reliably, and in accordance with human values. Implement safety filters, monitoring systems, and red-teaming pipelines that prevent harmful outputs and detect unsafe behaviour.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 55% Team / 45% Solo
- Client facing
- Rarely
- Impact visibility
- Very High
- Travel
- 5 to 10% for conferences
- Schedule flexibility
- Flexible
- Remote work
- Mostly Remote
- Typical work hours
- 45 to 55 hours/week
- Stress level
- High
At a glance
- Median salary
- $175,000
- Entry-level
- $125,000 - $155,000
- Senior
- $240,000+
- Growth by 2033
- 40% (much faster than average)
- Demand
- Growing Fast
- Freelance potential
- Very Low
- Salary growth potential
- High - 70 to 90% growth from entry to senior
- Typical student debt
- $20,000 - $60,000
Skills you'll use
Hard skills
- Python
- Safety evaluation
- Red-teaming
- LLM fine-tuning
- RLHF
- Monitoring systems
- Statistical analysis
Soft skills
- Analytical thinking
- Intellectual curiosity
- Ethical reasoning
- Attention to detail
- Communication
Technical complexity: Very High
How to get there
- Minimum education
- Master's Degree
- Licensing
- No
- Years to mid-career
- 3 to 5 years
- Years to senior
- 6 to 9 years
- Career switching
- Hard
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- ML Engineer > AI Safety Engineer > Senior AI Safety Engineer > Staff Safety Engineer > Principal Safety Engineer
Future outlook
- Automation probability
- 8% extremely low risk as safety judgment requires human values and expertise
- AI disruption risk
- Low
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 8.5/10
- Meaning
- 9.2/10
- Work-life balance
- 6.8/10
- Prestige
- 8.5/10
- Social perception
- Very High