Sovereign AI is a UK-based AI infrastructure and solutions provider building the next generation of sovereign-grade AI data centres across EMEA. Designed for resilience, security, and scale, Sovereign AI enables commercial and government customers to deploy advanced AI with confidence in environments where performance, reliability, and compliance are non-negotiable. Focused on regulated and mission-critical sectors including Government, Defence, Healthcare, and Financial Services, Sovereign AI is creating the trusted foundations for AI adoption at scale, combining robust infrastructure with disciplined governance to support long-term innovation and national-level capability.
KEY ACCOUNTABILITIES
Load Forecasting: Develop and maintain predictive models to forecast half-hourly load profiles for data centre sites, specifically accounting for high-density AI and hyperscale workloads.
Technoeconomic Modelling: Run financial and technical feasibility models (TCO, NPV, IRR) for connections, onsite generation (gas/firming), Battery Energy Storage Systems (BESS), and power purchase agreements (PPAs).
Site Due Diligence: Perform energy-specific commercial due diligence on prospective data centre locations and build energy pricing models factoring in local tariffs and connection costs.
Asset Optimization: Model the financial viability of market-facing opportunities, including Demand Response, virtual power plants (VPPs), and ancillary grid services.
Sustainability & Metrics Reporting: Design and track energy performance KPIs across the portfolio to support carbon accounting (Scope 1, 2, 3)
QUALIFICATIONS
Education: Bachelor’s degree in engineering, Economics, Finance, Mathematics, or a related highly quantitative field.
Advanced Degree (Preferred): Master's degree in Energy Systems or an equivalent technical discipline.
EXPERIENCE AND SKILLS
Experience building asset-level technoeconomic models (NPV, IRR, TCO) and performing time-series data analysis on large energy datasets to support long term capacity planning.
Advanced proficiency in Excel, SQL, and at least one programming language (Python or R) for data manipulation and statistical forecasting.
Solid understanding of deregulated power markets and commercial power purchase agreement (PPA) mechanics.
Experience reading, dissecting, and modelling industrial utility tariff structures and regulatory rate cases.
Ability to translate complex data into clear metrics for executive leadership.
