AI-Native Data Engineer

TL;DR

AI-Native Data Engineer: Building and optimizing high-reliability data pipelines and AI infrastructure for an energy management platform with an accent on time-series energy data, billing, and LLM workflows. Focus on architecting scalable GCP infrastructure, automating workflows with coding agents, and ensuring fast, clean shipping through CI/CD and observability.

Location: Hybrid in SF Bay Area (3 days onsite, 2 remote)

Company

hirify.global is building an AI Energy Agent to help businesses manage power costs, backed by top Silicon Valley investors.

What you will do

• Build high-reliability data pipelines and APIs for utility and public energy sources.
• Architect databases and ingestion systems for time-series energy data, billing, and telemetry.
• Design scalable and cost-efficient GCP infrastructure (BigQuery, Cloud SQL, Secret Manager).
• Build infrastructure to enable coding agents and AI tools for workflow automation.
• Set up CI/CD, observability, and automation for rapid, clean deployments.
• Document and communicate technical work, translating it into business impact metrics.

Requirements

• Must be AI-native, curious, and excited about LLMs and agents in real systems.
• Must be a nimble builder, able to ship MVPs quickly and iterate into robust solutions.
• Experience building production data systems with Python, TypeScript, GCP, and SQL/NoSQL.
• First-principles thinker, choosing tools based on logic, not hype.
• Strong communicator, able to explain work to both engineers and executives.
• Independent executor, defining, scoping, and delivering tasks without handholding.

Culture & Benefits

• Real ownership and significant impact at an early-stage startup.
• Opportunity to design long-lasting systems and see work ship rapidly.
• Work with a fast-moving team focused on first principles and customer/grid/planet impact.
• Shape the company's vision to redefine energy management for businesses.