Strategic Projects Lead - AI Safety
Reinforced Learning
2 hours ago
Full-time
On-site
Niagara Falls, New York, United States
Manager
Responsibilities
- Project and client management: Partner directly with the safety, alignment, and trust & safety teams at frontier AI labs — scoping their hardest data problems, translating them into deliverable programs, and driving revenue.
- Manage expert teams: Recruit and lead specialized contributors — red teamers, security researchers, trust & safety practitioners, and domain risk experts — and hold a high bar on the quality of what they produce.
- Shape how frontier models are made safe: Design the specifications behind adversarial datasets, jailbreak and attack taxonomies, refusal-boundary and over-refusal sets, and safety benchmarks that labs use to measure and improve model behavior.
- Build the red teaming machinery: Stand up repeatable methodologies — human red team campaigns, automated attack generation, coverage tracking against harm taxonomies — rather than one-off deliverables.
- End-to-end execution: Own projects from first conversation through final delivery, in a fast-moving environment where the spec often does not exist yet.
- Operational impact: Support initiatives across building, analysis, coordination, and execution as we scale the safety practice.
- 2+ years in AI safety, red teaming, trust & safety, adversarial ML, or security research; at a frontier AI lab, FAANG, top security firm, or equivalent.
- Hands-on adversarial experience: jailbreaking or stress-testing frontier models, prompt injection research, offensive security, penetration testing, bug bounty, CTFs, or trust & safety investigations and enforcement.
- Fluency with how safety work is actually structured (harm taxonomies, evaluation design, safety frameworks and model policy).
- High agency and the ability to execute in ambiguity; comfort defining the problem before solving it.
- Strong writing. Much of this job is specifying risk precisely enough that fifty other people can execute against it.
- Genuine passion for AI and interest in entrepreneurship.
- Demonstrated track record of competitive success.
- Strong leadership and communication skills.
- Python proficiency and the ability to write production-quality code.
- Published safety, alignment, or security research.
- Track record in bug bounty, CTF, or model red teaming competitions.
- Experience building automated red teaming or eval pipelines.
- Depth in a high-consequence risk domain (cyber, bio, fraud and financial crime, child safety, influence operations).
- Experience using AI tools to automate workflows and build products.