Join Powerline and help build the future of autonomous energy systems.

Powerline is a fast-growing, VC-backed climate tech company transforming how renewable energy and battery storage assets operate on the electricity grid. Our technology combines machine learning, optimization, and market intelligence to help asset owners monitor, analyze, and maximize operational performance in the world’s most complex energy markets.

We work with leading developers, traders, and operators across global electricity markets, solving high-impact problems that accelerate the transition to a more flexible, decarbonized grid.

About the Role

We are looking for a Lead AI Engineer to design and build an agentic system that can reason over complex data, orchestrate modeling workflows, and autonomously generate insights and decisions related to energy asset operations.

This role focuses on building production-grade AI systems used by experts in energy markets. You will develop systems that combine LLMs, time-series data, and optimization engines into intelligent agents that operate across both: Interactive workflows and Autonomous workflows. You will play a foundational role in defining how AI systems understand and interact with energy assets and electricity markets.

What You’ll Build

You will design and deploy Powerline’s AI Agents to:

1. answer complex questions, explain algorithm results, and act as a decision-support tool;
2. run continuous tasks and be proactive, without human intervention; and
3. iterate, evaluate, and inference with Powerline data and infrastructure

These systems will operate in high-stakes environments where correctness and reliability directly impact economic decisions.

Core Responsibilities

• Architect and build agentic AI systems that plan, reason, and act across workflows
• Design tool-using agents that integrate with Powerline systems
• Develop multi-step decision systems
• Build stateful and long-running agents
• Define and implement evaluation frameworks
• Improve reliability, observability, and safety of LLM-based systems in production
• Collaborate with energy market specialists to translate real-world workflows into