ON. energy
Energy
AIEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Engineer at ON. energy. Skills: AI Engineer, production AI systems, LLM-powered features, software engineering fundamentals. Building production AI systems end to end, from prototype through deploy and monitor. Working directly with stakeholders across Engineering, Operations, HR, Finance, and Commercial to translate workflow problems into shippable tools”
Industry & Context.
translate workflow problems into shippable tools; Comfortable in ambiguity. We don't have a fully scoped you'll help build it
hands-on builder role with high visibility, work will be in front of executives regularly, systems you ship will touch most of the company within your first year
What They're Looking For.
Must Have
hands-on production experience building AI/ML systems, Demonstrated ability to ship: a portfolio of projects or work history that shows you take things from idea to running system, not just notebooks, Solid software engineering fundamentals, including version control, testing, code review, and deployment practices, Working knowledge of modern AI tooling: LLM APIs, RAG, evaluation, agent frameworks, vector stores, written and verbal communication, Comfortable in ambiguity
Nice to Have
Production experience with hosted LLM platforms (Anthropic API, Azure OpenAI, AWS Bedrock, or equivalent), Hands-on experience with Claude Code, MCP server development, or agentic coding tools, Familiarity with Microsoft ecosystem integration (Entra ID, Graph API, M365 surfaces) for enterprise AI deployments, Experience with agent orchestration frameworks or multi-agent systems, Exposure to settings where data sensitivity and operational safety constrain what you can deploy (OT, healthcare, finance, regulated industries), Background in energy, utilities, or other operationally complex sectors
What You'll Do.
Building production AI systems end to end
from prototype through deploy and monitor
Working directly with stakeholders across Engineering
and Commercial to translate workflow problems into shippable tools
Writing the evaluation harnesses
and integration code that make LLM-powered features reliable
Establishing reusable technical patterns: prompt and model governance
Contributing to the technical roadmap
including where to invest
and what's worth building in-house versus buying
Supporting the Program Manager on technical scoping for new use cases
including calling out when an out-of-the-box tool will solve the problem versus when custom work is justified
How You'll Work.
Team & Collaboration
Partner closely with our Program Manager, AI Enablement; Working directly with stakeholders across Engineering, Operations, HR, Finance, and Commercial
Communication Scope
written and verbal communication; You'll be in front of non-technical stakeholders regularly and the work needs to translate
Process & Methodology
Contributing to the technical roadmap
Full Job Description
ON.energy is building the power infrastructure that makes the AI era possible. As AI demand surges past what the grid and traditional data centers can support, ON.energy provides a new class of power technology proven at gigawatt scale and trusted by the world’s leading cloud and AI companies. Our systems are already deployed across 2.5 GW of hyper-scale campuses, validated by top U. S. national labs, and certified for grid-safe operation by major utilities. With real products in the field, we’re scaling faster than the grid can, transforming power from a bottleneck into a competitive advantage for the companies building the future. ON.energy is investing in AI as a horizontal capability across the business, from corporate functions to field operations and OT environments. We're standing up a small team to drive adoption, and we're hiring an AI Engineer to build the systems that make it real. You'll partner closely with our Program Manager, AI Enablement, who owns the roadmap and drives adoption across departments. Your job is to ship: prototype quickly, harden what works, and build the technical patterns the rest of the company will reuse. This is a hands-on builder role with high visibility. The CTO is the executive sponsor for AI Enablement, your work will be in front of executives regularly, and the systems you ship will touch most of the company within your first year. Responsibilities Will Include: Building production AI systems end to end, from prototype through deploy and monitor Working directly with stakeholders across Engineering, Operations, HR, Finance, and Commercial to translate workflow problems into shippable tools Writing the evaluation harnesses, prompts, retrieval logic, and integration code that make LLM-powered features reliable Establishing reusable technical patterns: prompt and model governance, eval frameworks, data access, deploy practices Contributing to the technical roadmap, including where to invest, what to kill, and what's worth buil
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