Confidential mandate

AI Model Evaluation & Safety Authority — Frontier-Model Recovery

Urgent / Unplanned

AI Model Evaluation & Safety Authority mandate in Bengaluru, India · Frontier Artificial Intelligence

A frontier-model startup needs an interim safety authority to establish evaluation governance, support investor confidence and leave three independently evidenced model gates operating within nine months.

The mandate

The company requires structured evaluation governance for its bilingual coding model and future releases, with release authority to be established independent of the product council.

The interim must be available within fourteen days and will hold the executive safety seat for nine months. A global search for a permanent leader begins after the new evaluation architecture survives its first external replication in month four; the contract includes a thirty-day successor overlap and will not extend if the search slips.

Handover is achieved when every production model has a version-linked evaluation record, leakage-controlled benchmark suite and documented deployment boundary; two independent red teams have closed critical findings; and three consecutive release councils have applied the same evidence threshold without founder exception. The permanent appointee must then chair a complete review and accept the residual-risk register.

The interim may block any candidate release, quarantine suspect evaluation data, allocate sanctioned evaluation compute, commission specialist testing within a ₹4 crore envelope and appoint temporary incident leads. Changes to the board’s risk appetite, external disclosure of vulnerabilities, expenditure above that ceiling and permanent appointments require board approval; the interim may not amend fundraising representations or publish model weights.

Core model architecture, consumer-product pricing and the next capital raise are outside this assignment. The seat may require evidence from those workstreams, but it does not own research-roadmap selection, enterprise contracting or remediation of unrelated software-security debt.

Why this seat is open

The disputed release exposed a safety function whose veto existed on paper but could be reversed without recorded evidence. Neither founder can occupy the role credibly while the board examines the incident and prospective investors test governance. An independent operator is needed to rebuild the release system before a permanent appointment is made.

What you will own

  • Ratify a release-evidence standard that links each model’s threat assumptions, capability claims, deployment boundary and residual risk to reproducible evaluation results.
  • Authorise, condition or block candidate releases through written decisions that identify failed thresholds, compensating controls and the evidence required for reconsideration.
  • Reconstruct the contaminated benchmark lineage and decide which historic performance claims must be withdrawn, restated or retested against protected holdouts.
  • Stage adversarial evaluations covering autonomous tool use, multilingual misuse, code execution, data exfiltration, deceptive behaviour and loss of operator control.
  • Convene a model-risk council with protected escalation routes, declared dissent, conflict records and an explicit prohibition on undocumented founder overrides.
  • Commission two independent replications and reconcile material variance between internal scores, external findings and behaviour observed in enterprise pilots.
  • Transfer the evaluation registry, compute plan, unresolved research questions, incident playbooks and first ninety-day agenda through a witnessed successor review.

Candidate qualifications

  • Held chief safety, model assurance or enterprise evaluation authority inside a frontier-model laboratory or an advanced AI platform releasing foundation models.
  • Personally withheld or constrained a consequential model release and can evidence the technical threshold, executive challenge and subsequent disposition.
  • Designed evaluation harnesses spanning capability measurement, adversarial robustness, agentic action, multilingual performance and post-deployment monitoring.
  • Investigated benchmark leakage or training-data contamination deeply enough to separate genuine capability movement from invalid measurement.
  • Presented model-risk evidence directly to boards, investors or public authorities while protecting sensitive methods and unresolved vulnerabilities.
  • Completed a leadership transition in a founder-led environment where safety independence, commercial urgency and scarce evaluation compute were in active tension.

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This mandate is confidential. The client is named only under a mutual NDA, and your own record is never listed, sold or shown to a company under your name until you release it for this specific mandate.