Principal Backend Architect for AI & Time-Series Energy

CVector - Industrial AI; New York (NY); On-site; USD 190,000 - 270,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Health Flexible Spending Account (FSA)

Unlimited PTO

Modern developer stack equipment

Unlimited access to AI agent systems

Visa sponsorship for US-based hires

Job summary

CVector - Industrial AI in New York City seeks a Principal backend engineer to evolve our core platform. You will own time-series data systems, AI-assisted analytics, cloud infrastructure, and data ingestion pipelines powering customer applications and modeling tools.

You will collaborate with product, modeling, and frontend teams, make architectural decisions, drive migrations, and scale intelligence across industrial energy workflows, while shaping platform direction and reliability.

Qualifications

• decade+ of experience building and operating production backend systems.
• Built and maintained multiple generations of distributed systems.
• Tracking latest developments in agentic system design and AI platforms.

Responsibilities

• Own and evolve the core backend platform and time-series data systems.
• Develop and maintain AI-assisted analytics, cloud infrastructure, and data ingestion pipelines.
• Collaborate with product, modeling, and frontend engineers; influence platform direction, reliability, and scalability.
• Drive major migrations and shape how intelligence is embedded into industrial energy workflows.

Skills

Time-series systems

Distributed backend

AI analytics

Cloud infrastructure

Data ingestion pipelines

Python

TypeScript

PostgreSQL

Tools

Supabase

PostgreSQL

MQTT

TigerData

AWS

GitHub CI/CD

Job description

CVector - Industrial AI in New York City seeks a Principal backend engineer to evolve our core platform. You will own time-series data systems, AI-assisted analytics, cloud infrastructure, and data ingestion pipelines powering customer applications and modeling tools.

You will collaborate with product, modeling, and frontend teams, make architectural decisions, drive migrations, and scale intelligence across industrial energy workflows, while shaping platform direction and reliability.