OpenAI is hiring a $555,000 head of preparedness to tackle AI risks from mental health to cybersecurity

OpenAI is hiring a Head of Preparedness. Here's what it means for your AI strategy

OpenAI is recruiting a "head of preparedness" to lead its safety systems team with a stated mission: make sure advanced models are built and deployed responsibly. The role pays $555,000 and centers on tracking high-end model risks and building mitigation plans for "frontier capabilities that create new risks of severe harm."

"This will be a stressful job and you'll jump into the deep end pretty much immediately," CEO Sam Altman said in a weekend post. He noted that models are improving quickly and bringing real challenges alongside their benefits.

The move follows rising concern over AI's influence on mental health, including lawsuits alleging harmful interactions with chatbots and new protocols from OpenAI for users under 18. There's also growing alarm around AI-enabled cyberattacks as low-cost tools make sophisticated tactics more accessible to non-state actors.

Altman has also acknowledged that models are getting good enough at computer security to find critical vulnerabilities. He called for better ways to measure how capabilities could be abused and how to limit downsides while keeping the upside.

Why executives should care

• Signal to the market: AI risk and safety are now executive-level responsibilities with real budgets, headcount, and accountability.
• Product velocity vs. safety: Speed without evaluations, guardrails, and incident response invites legal, reputational, and security fallout.
• Customer trust: Enterprise buyers will demand evidence of testing, monitoring, and responsible-use controls before signing.
• Regulatory direction: Requirements are coalescing around governance, documentation, and evaluation. Early movers avoid fire drills later.

What a Head of Preparedness actually does

• Define a risk taxonomy for misuse, safety, security, privacy, and content harms across your model and application stack.
• Stand up high-rigor evaluations and red teaming for jailbreaks, data leakage, hallucinations, and code exploitation.
• Own model and app-level safety reviews, rollout gates, kill switches, and incident playbooks.
• Continuously monitor post-deployment behavior, abuse patterns, and drift; ship fixes fast.
• Coordinate with security, legal, compliance, product, and comms; brief the board on risk posture and incidents.
• Drive vendor assessments for third-party models, plugins, and data providers.
• Set safeguards for youth and vulnerable users, with escalation to human support when needed.

Action plan for the next two quarters

• Stand up an AI Risk Committee with clear RACI across product, security, legal, support, and PR.
• Adopt a recognized framework and translate it into controls, tests, and artifacts:
  • NIST AI Risk Management Framework
  • CISA Secure by Design
• Build an evaluation pipeline: adversarial prompts, disallowed content checks, factuality tests, and security-focused LLM red teaming.
• Gate launches on passing thresholds; require sign-offs from security and legal for high-risk use cases.
• Harden data paths: least-privilege access, secrets isolation, PII minimization, and logging for auditability.
• Set age-appropriate use policies, filters, and escalation to human help for distress or self-harm signals.
• Vendor risk: classify providers by risk, require eval results and SOC/ISO attestations, and negotiate model misuse SLAs.
• Run incident simulations for prompt injection, model exploit, and harmful content; measure time to detect and time to contain.
• Publish a responsible AI statement and acceptable-use policy; train customer-facing teams on responses and escalation.

Hiring signals and org design

OpenAI's posting calls for deep technical expertise in machine learning, AI safety, evaluations, security, or adjacent risk domains. It also emphasizes experience running high-rigor evaluations for complex technical systems.

If you're early, start with a director-level lead reporting to the CTO or CISO with a dotted line to the board. As risk surface grows, evolve to a dedicated head with budget, a cross-functional mandate, and authority to block launches.

KPIs that matter

• Eval coverage across priority risks and models
• Jailbreak success rate and mean time to patch
• Incidents per 10K interactions and time to contain
• Security findings related to model use and remediation cycle time
• Vendor risk scores and audit pass rates

Budget guardrails

• People: Head of preparedness, red teamers, eval engineers, policy lead, incident manager.
• Tools: Prompt/agent testing, content safety services, code scanning, secrets management, logging/telemetry.
• Programs: Bug bounty for model behavior, external audits, tabletop exercises.

Where to upskill your team

• AI courses by job role to ramp product, security, and legal teams.
• Popular AI certifications to signal baseline competence across the org.

Bottom line

OpenAI's hire is a clear signal: AI safety leadership is now table stakes for any company deploying advanced models. Treat preparedness as a product function with hard metrics, blocking power, and direct ties to the board. Move now, or the market and regulators will make the decisions for you.