We are hiring a Strategic Partnerships Lead to own day-to-day partnerships with frontier model developers. This is a hands-on role for someone who is technically curious, comfortable with researchers, and operationally rigorous. You will partner closely with research, operations, and go-to-market.

The team

Red Team and Safety is a nimble function that stress-tests frontier AI. We partner with major model developers to generate adversarial data, run evaluations, and publish benchmarks across jailbreaks, prompt injection, agentic misuse, LLM-based cyber security, CBRN, political bias, and self-harm. Our work shapes how leading labs train their models and how governments and enterprises deploy them.

You will:

• Own a portfolio of frontier-lab partnerships day-to-day. Run customer conversations, scope new engagements, and grow accounts from one-off projects into ongoing scope.
• Act as a credible subject-matter expert in customer conversations; explain adversarial methodology, vulnerability taxonomies, benchmark findings, and what they imply commercially, in language that lands with technical buyers.
• Partner with Enterprise and Public Sector account teams to qualify and close opportunities where safety, red teaming, or LLM-based cyber security are part of the deal.
• Coordinate delivery with research and operations leads. Make sure scope, capacity, and timelines line up before we commit, and unblock the team as engagements run.
• Contribute to public benchmark launches. Help shape the framing, the rollout, and the narrative we take to customers and the field.
• Feed signal back into the roadmap. Surface what customers are asking for, what is breaking, and what we should build next.

Ideally, you would have:

• Working fluency in model behavior, adversarial ML, and AI safety, enough to hold a substantive conversation with researchers and ML engineers.
• Experience managing technical accounts or partnerships, ideally with frontier AI labs, large enterprises, or federal agencies.
• Genuine interest in AI safety, evidenced in prior work, writing, or research.
• Strong written and verbal communication and the ability to translate between research and commercial audiences.
• Operational rigor; you scope carefully, track commitments, and keep complex engagements moving.
• Comfort with ambiguity and a bias toward action.

Nice to haves:

• 2+ years of relevant experience.
• Hands-on red teaming, penetration testing, or adversarial ML experience.
• Background at a frontier AI lab, AI policy organization, or national security agency.
• Experience contributing to public benchmarks, evaluations, or research publications.
• Advanced degree in a relevant technical field.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You9ll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting9s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$152,000-$190,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.