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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 Engineer, you will evolve CVector's core backend platform, working on time-series data systems, AI-assisted analytics, cloud infrastructure, and data ingestion pipelines that power customer-facing applications and internal modeling platforms. This role sits at the intersection of AI systems, distributed databases, and real-world industrial infrastructure.
You will take ownership of complex systems, drive major technical migrations, and shape how intelligence is embedded into industrial energy workflows. You will collaborate closely with product, modeling, and frontend engineers, with significant influence over platform direction, reliability, and long-term scalability. Your work directly impacts system reliability, customer trust, and CVector's ability to scale intelligent energy management across industries.
The role is ideal for an engineer who enjoys working close to data and infrastructure layers, has strong architectural judgment, and is excited to operate across AI systems, databases, and distributed backend services. You will solve deep backend problems, shape platform foundations, and embed intelligence into physical systems.
Technology stack: Python, TypeScript, Supabase, PostgreSQL, MQTT, TigerData, AWS, and GitHub-based CI/CD workflows. The position is based in the New York City office, four days per week.
REQUIREMENTS:
- A decade or more of experience building and operating production backend systems
- Track record of building and maintaining multiple generations of distributed systems
- Demonstrated impact and influence in your corner of the industry; ambition to replicate that at CVector
- Familiarity with latest developments in agentic system design, with readiness to grow a leading-edge system
- Proficiency with Python, TypeScript, or similar backend languages
- Experience with cloud infrastructure (AWS), databases (PostgreSQL), and distributed systems
