Lead the evolution of CVector’s core backend platform, focusing on AI-driven analytics, cloud infrastructure, and data pipelines for real-time energy optimization. Own complex systems, drive technical migrations, and shape intelligent decision-making workflows for industrial energy management. Collaborate with cross-functional teams to ensure scalability, reliability, and platform innovation.
Key Highlights
Architect and maintain distributed backend systems for AI-assisted analytics and real-time decision-making in energy/manufacturing
Drive major technical migrations and influence platform direction with deep expertise in time-series data and cloud infrastructure
Work at the intersection of AI systems, databases, and industrial energy workflows with direct impact on system reliability and customer trust
Key Responsibilities
Design and optimize CVector’s core backend platform for AI-driven time-series data processing and real-time optimization
Develop and maintain cloud infrastructure, data ingestion pipelines, and distributed systems for industrial energy applications
Collaborate with product, modeling, and frontend teams to integrate AI systems with live asset constraints and market dynamics
Drive technical migrations and ensure platform scalability, reliability, and long-term performance
Shape the integration of intelligence into physical energy/manufacturing systems with measurable business impact
Technical Skills Required
Python
Distributed Systems
Cloud Infrastructure (AWS)
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Benefits & Perks
Competitive compensation with meaningful equity upside
Unlimited PTO (minimum 3 weeks + sick days)
Visa support for US-based candidates (including employer-sponsored visas)
Nice to Have
Experience with agentic system design
Expertise in MQTT, Supabase, PostgreSQL, or TigerData
TypeScript or GitHub-based CI/CD workflows
Job Description
CVector's mission is to bring real time economic optimization and AI prediction to every energy and manufacturing plant.Industrial facilities make decisions every minute that determine cost, reliability, and margin, but the signals that matter live in different worlds: live asset constraints and process reality on one side, feedstock prices, product prices, demand, and market dynamics on the other. We fuse those worlds into one decision layer that continuously forecasts what is coming, simulates what could happen, and optimizes what to do next, so plants can run closer to their true economic potential every day.This position works from our
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