AI Engineer

Palo Alto, CAHybridFull TimePosted 19 days ago

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Required skills

AI Agents
LLMs
time-series data
optimization engines
Python
APIs
external systems
multi-step systems
stateful systems
memory frameworks

Nice to have

partial autonomy
full autonomy
real-world environments
real-time data
streaming data pipelines
electricity markets

Role summary

Powerline, a climate tech company, seeks a Lead AI Engineer to design and build an agentic system for autonomous energy systems. This role involves creating production-grade AI agents that combine LLMs, time-series data, and optimization engines to operate in interactive and autonomous workflows within high-stakes energy markets. Responsibilities include architecting agentic systems, developing multi-step and stateful agents, defining evaluation frameworks, and improving LLM system reliability. The ideal candidate has strong Python skills, experience with RAG and agent orchestration frameworks, and a passion for building 0→1 systems in a fast-paced environment.

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:
answer complex questions, explain algorithm results, and act as a decision-support tool; run continuous tasks and be proactive, without human intervention; and 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 agent behavior and logic Help lead technical direction for agent architecture and system design

Requirements

Experience building production AI or software systems, including work with LLM-powered or agentic applications
Strong Python skills and experience integrating with APIs and external systems
Experience designing multi-step or stateful systems (e.g., pipelines, workflows, or agents)
Experience building memory and Retrieval Augmental Generation (RAG) frameworks
Experience with Agent evaluation from direct user feedback
Experience with Agent orchestration frameworks (e.g., Pydantic AI, LangChain, or similar)
Ability to operate across engineering, product, and applied AI
Strong ownership mindset and comfort building 0→1 systems in fast-paced environments
Excellent communication skills and ability to collaborate across technical and domain teams
Strong Plus — Experience building systems with partial or full autonomy in real-world environments
Experience working with real-time or streaming data pipelines
Experience in electricity markets, trading, or energy systems
Experience with time-series modeling or forecasting
Experience with optimization systems

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