Legal Case Study Author (AI Training)

Author regulatory and compliance decision cases grounded in EU law (GDPR, EU AI Act, DORA, MiCA) that train and evaluate frontier AI models. $500 per approved case. Remote.

About the role Sovrano AI builds evaluation and training environments for frontier AI models. We are hiring domain experts to author real-world case studies that become the human reference an AI model is measured against. Each case is a paid, self-contained piece of work: you author it, our reviewers assess it, and you are paid on approval.

This role has immediate paid work: $500 for each approved case study (case brief plus data room). Approved authors will also be among the first experts we reach out to when relevant opportunities arise, with access to future projects available through our expert network.

For this role the cases are regulatory and compliance decision scenarios under EU frameworks: GDPR, the EU AI Act, DORA, MiCA, NIS2, MiFID II and adjacent regimes. The decision-maker is typically a General Counsel, DPO, Head of Compliance, or an executive committee acting on their advice.

Key responsibilities Author a complete case built around a real decision at a real company, from scoping through submission. Write the case study brief: a firm-and-role persona (never your own name), the audience and the decision in front of it, and a real company (listed EU with public data, or private with disclosed financials) with a one-line justification of why it supports a verifiable decision. Build the thesis as 3 to 5 bullets, each carrying a number, plus a preliminary recommendation with a number, flagged as contingent on the analysis. Set out the scoped deliverable plan and the assumptions approach: sources named tier by tier, every assumption labeled sourced or estimated, and a pinned as-of date for the data. State the weakest point of your own case, and its mitigant. Assemble a slim data room: 10 to 20 distinct, relevant documents behind a single index. Prefer real public documents. Where an internal figure is genuinely undisclosed, construct a clearly labeled case-data extract anchored to a cited public benchmark. Make every number in the case trace to a data-room document. Anchor each case on a live compliance decision with resources and consequences attached: whether a product launch is compliant and under what conditions, the risk classification of an AI system under the EU AI Act and the obligations that follow, a DORA ICT third-party remediation decision, whether a token or service falls in scope of MiCA and the licensing consequence, or a cross-border data-transfer decision after a regulator ruling. Purely academic or overview-of-the-law topics are rejected. Cite real regulations at article level (for example Art. 6(1) and Annex III EU AI Act, or Art. 28 GDPR) and real regulator materials: EDPB guidelines, ESMA and EBA statements, published enforcement decisions. Include an in-scope justification line in the brief: why this company and this decision sit inside the named regulatory framework. Draw the data room on regulation excerpts, regulator guidance and enforcement decisions, company disclosures and policies, and clearly labeled internal-style extracts where needed.

Ideal qualifications Law degree (LLB, LLM, JD or equivalent), or a compliance-focused degree with demonstrable legal-regulatory work. 2 to 3 years of non-academic experience in legal practice, regulatory compliance, data protection, or financial-services regulation. Working command of at least two of GDPR, EU AI Act, DORA, MiCA, NIS2 and MiFID II, with the ability to cite them at article level. Professional English, and the ability to write precise, decision-oriented legal analysis for an executive audience. Fully remote. You work on your own schedule against an agreed submission date.

Requirements

• Law degree (LLB, LLM, JD or equivalent) or compliance-focused degree with legal-regulatory work experience

• Minimum 2 years of non-academic legal, regulatory, compliance or data-protection experience

• Working command of at least two of GDPR, EU AI Act, DORA, MiCA, NIS2, MiFID II

• Able to cite regulation at article level

• Professional English

• Human-authored work only, with no AI use anywhere in the case (file metadata is verified)

• Available for a short live walkthrough call during assessment

• Remote, working to your own schedule against an agreed submission date

Nice to have In-house experience as, or alongside, a General Counsel, DPO, or Head of Compliance. Hands-on work with published enforcement decisions or regulator correspondence. Advisory experience on AI systems, ICT third-party risk, or crypto-asset licensing. Prior work authoring teaching cases, training material, or AI evaluation data.

What success looks like Your case is human-authored end to end, with no AI use anywhere in it. File metadata is verified. The decision at the center of the case is real, in scope, and consequential, not an overview of the topic. Every number is internally consistent and reconciles to a document in the data room. You walk a reviewer through a number and an assumption of our choosing on a short live call, and both hold up. The data room stays slim and relevant: 10 to 20 documents, one index, no filler. Your case is approved on the first pass, or after one revision cycle against specific feedback.

Payment terms $500 flat per approved case study (brief plus data room), paid on approval rather than on submission.

Approval follows the Sovrano review gates. If a case needs work you get one substantive revision cycle with specific feedback.

Additional cases by mutual agreement after your first approval, at the same rate.

Fully remote contract work. You set your own schedule against an agreed submission date.

How to apply: apply here with your CV or LinkedIn profile and 2 to 3 sentences on the decision scenario you would author first, covering the company, the decision, and why you know this ground. Shortlisted applicants receive the full case authoring guidelines and template, and a short intro call before starting.

Location: Remote (European Union)