Lead the evolution of CVector's core backend platform, focusing on time-series data, AI‑assisted analytics, and cloud infrastructure. Own complex distributed systems, drive major technical migrations, and ensure reliability and scalability. Require 10+ years of production backend experience, strong architectural judgment, and expertise in Python, AWS, and SQL databases.
Key Highlights
Design and build scalable backend services for real‑time energy optimization.
Integrate AI infrastructure and time‑series data pipelines across cloud platforms.
Collaborate with product, modeling, and frontend teams to shape platform direction.
Key Responsibilities
Evolve and maintain CVector's core backend platform for real‑time economic optimization.
Develop and operate time‑series data systems, AI‑assisted analytics, and data ingestion pipelines.
Design cloud infrastructure solutions on AWS to support scalable, reliable services.
Take ownership of complex distributed systems and lead major technical migrations.
Shape platform reliability, scalability, and long‑term architectural direction.
Collaborate closely with product, modeling, and frontend engineering teams.
Technical Skills Required
Python
Amazon Web Services
SQL
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Benefits & Perks
Competitive compensation with equity upside
Comprehensive health, dental, and vision insurance
Unlimited PTO with a minimum of three weeks per year
Top‑of‑the‑line work equipment and high‑performance laptops
Visa support and employer‑sponsored visa applications for US candidates
Nice to Have
Familiarity with agentic system design and emerging AI infrastructure trends.
Experience with TypeScript, Supabase, MQTT, TigerData, and GitHub 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.
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