Energy Regulatory Counsel

micro1 is engaging experienced Energy Regulatory Counsels to contribute to a customer’s AI training initiative.

In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

We’re looking for attorneys with substantive experience advising utilities, independent power producers, or energy regulators on rate design, market structure, and regulatory compliance.

Scope of Work

1. Contribute expert-level legal reasoning on energy and utilities regulatory questions, including rate design, tariff structure, and compliance obligations.
2. Work through realistic regulatory scenarios drawn from FERC, state PUC, and ISO/RTO practice, explaining the analysis behind your conclusions.
3. Identify where a question is unsettled, jurisdictionally contested, or turns on facts that change the answer.
4. Review and validate work from other contributors for legal accuracy and clarity of reasoning.
5. Document your reasoning clearly, so the analysis is as useful as the conclusion.
6. Flag ambiguous or poorly framed scenarios to project coordinators instead of resolving them silently.
7. Deliver assigned work on schedule and at the required quality level.

Required Qualifications

1. J.D. from an ABA-accredited law school and active U.S. bar admission.
2. 4+ years of substantive energy and utilities regulatory practice — hands-on, not supervisory-only or adjacent exposure.
3. A corporate law foundation, ideally built at a Vault 100 firm.

How the selection process works

1. Apply and complete the screening questions
2. Complete the AI interview — this is how we showcase your expertise to the client
3. Profile review
4. Onboarding — our Talent Ops team will get you set up

About micro1

micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.

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