Data Center Energy Lead
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Role details
Tech stack
Job description
Anthropicās Infrastructure team is seeking a Data Center Energy Lead to secure power capacity and accelerate energy delivery for our rapidly expanding AI compute footprint. Youāll work at the intersection of energy markets, utility operations, and AI infrastructure needs, leading multi-hundred megawatt procurement efforts and building strategic relationships with utilities, grid operators, and regulators across multiple jurisdictions. This role is essential to ensuring Anthropic can scale compute capacity efficiently while navigating complex energy market dynamics and regulatory environments to achieve the speed and scale required for frontier AI development., * Lead energy procurement and markets strategy to secure multi-hundred megawatt power capacity for AI infrastructure, structuring utility partnerships and commercial agreements that prioritize speed-to-energization and scale
- Own utility and regulatory stakeholder management across multiple jurisdictions, building strategic relationships with ISOs, transmission operators, and utilities to accelerate interconnection timelines and unlock constrained capacity
- Drive energy markets and policy strategy for AI compute facilities, monitoring regulatory developments and engaging policymakers to address grid capacity challenges and expedite approval processes for critical infrastructure
- Partner with engineering and delivery teams to translate energy market dynamics and utility constraints into actionable capacity acceleration strategies that align procurement schedules with aggressive project timelines
- Develop deep market intelligence on regional power availability, transmission constraints, and interconnection queue dynamics to inform site selection and deployment strategy
- Structure innovative commercial frameworks and partnership models that enable faster power delivery and mitigate grid capacity risks across Anthropicās datacenter portfolio
Requirements
- Have 15+ years of experience in energy procurement, utility development, or power markets for large-scale infrastructure projects
- Have deep expertise in wholesale power markets, utility interconnection processes, and transmission system planning
- Have experience securing 100+ MW of power capacity and navigating complex utility service agreements or power purchase agreements or other offtake agreement structures
- Are proficient in analyzing energy market dynamics, regulatory frameworks, and grid constraints to inform strategic decision-making
- Have strong stakeholder management skills and experience building relationships with utilities, ISOs/RTOs, regulators, policymakers and critical equipment vendors.
- Have excellent communication skills and can translate complex grid and regulatory dynamics into actionable business strategies for technical and non-technical audiences
Strong candidates may also have some of the following:
- Past experience with energy procurement specifically for datacenters, high-performance computing, or AI/ML infrastructure
- Familiarity with hyperscale infrastructure requirements and the unique power demands of large-scale AI training and inference workloads
- Experience with regulatory affairs, energy policy advocacy, or engagement with state/federal energy commissions (FERC, state PUCs)
- Background in transmission planning, interconnection study processes, or grid capacity analysis
- Understanding of emerging grid technologies (energy storage, demand response, distributed energy resources) and how they can accelerate capacity delivery
- Track record of structuring creative solutions to overcome grid constraints and compressed timelines in competitive power markets, Minimum education: Bachelorās degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Benefits & conditions
For sales roles, the range provided is the roleās On Target Earnings (āOTEā) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000-$485,000 USD, Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidatesā AI Usage: Learn about our policy for using AI in our application process.
About the company
Anthropicās mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems., We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. Weāre an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
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