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CVector is building real-time economic optimization and AI prediction systems for energy and manufacturing plants. The company fuses live asset constraints, process data, and market dynamics into a unified decision layer that continuously forecasts outcomes, simulates scenarios, and optimizes operations.
As Principal Software Engineer for Backend & AI Infrastructure, you will own the evolution of CVector's core backend platform. Your focus areas include time-series data systems, AI-assisted analytics, cloud infrastructure, and data ingestion pipelines that power customer-facing applications and internal modeling platforms. You will work close to data and infrastructure layers, driving major technical migrations and shaping how intelligence is embedded into industrial energy workflows.
You will collaborate with product, modeling, and frontend engineers, with significant influence over platform direction, reliability, and long-term scalability. This role sits at the intersection of AI systems, time-series data, and real-world energy infrastructure—your work directly impacts system reliability, customer trust, and CVector's ability to scale intelligent energy management across industries.
The current technology stack includes Python, TypeScript, Supabase, PostgreSQL, MQTT, TigerData, AWS, and GitHub-based CI/CD workflows. You will operate real-world systems in demanding industrial environments and work from the New York City office four days per week.
QUALIFICATIONS:
- A decade or more of experience building and operating production backend systems
- Track record of building and maintaining multiple generations of distributed systems
- Demonstrated ability to leave a fingerprint on your corner of the industry
- Familiarity with latest developments in agentic system design, ready to grow a leading-edge system
- Strong architectural judgment and ability to take ownership of complex systems
