Senior Software Engineer - Backend & AI Infra

About CVector CVector analyzes plant, application, and live market data to create dollar-scored recommendations so operators can act before opportunities are missed.

CVector

Connecting plant decisions to business outcomes

Industrial IoTData AnalyticsCarbon-intensityRenewable Energy Integrationand Facility Operations & Optimization

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C

cvector.com

11-50 employees

Data Infrastructure and Analytics

New York, NY

2024

Privately Held

5.5k LinkedIn followers

• As a Senior Software Engineer, you will contribute across several interconnected areas
• Map customer domains and operational workflows into effective prompts and AI system interfaces
• Design, execute, and iterate on evals for AI outputs
• Incorporate customer feedback and reinforcement signals to improve system behavior
• Refine context selection, retrieval, and trace collection to improve output quality
• Fine-tune smaller models using collected traces to reduce latency while preserving performance
• Evaluate and integrate new AI platforms and models as they become available
• Support training and deployment of large, time-series-focused models
• Lead migrations and upgrades of our time-series data schemas and storage engines
• Upgrade and maintain PostgreSQL and related database infrastructure
• Develop and maintain data connectors for industrial and third-party systems
• Lead MQTT-based data ingestion pipeline improvements
• Transition PostgREST to GraphQL-based framework and evolve our API architecture
• Improve TigerData to next-gen time series design and simplify multi-tenant provisioning workflows
• Optimize performance and reliability of high-volume time-series data stores
• Design and execute architecture plans for TigerData
• Augment analytical workloads using Parquet and/or Iceberg-based storage formats
• Balance real-time and historical query performance across operational and analytical use cases
• Enable parallelized and distributed model training workflows
• Implement message brokers and orchestration mechanisms for multi-stage learning pipelines
• Improve reproducibility, traceability, and coordination across modeling stages
• Strengthen cloud infrastructure uptime, observability, and deployment reliability
• Standardize build, test, and release processes across services
• Improve developer tooling and internal platform ergonomics
• Port backend services from bun to Node.js where appropriate
• Track and improve DORA metrics (deployment frequency, lead time, change failure rate, recovery time)
• Participate in an on-call rotation and continuously improve operational readiness

• Our current technology stack includes Python, TypeScript, Supabase, PostgreSQL, MQTT, TigerData, InfluxDB, AWS, and GitHub-based CI/CD workflows.
• A relevant engineering degree or equivalent professional experience with a strong computer science foundation
• 2+ years experience building and operating production backend systems
• Strong proficiency in Python and/or TypeScript for backend development
• Experience with databases, especially PostgreSQL and time-series or analytical data stores
• Familiarity with event-driven systems, streaming data, or message brokers
• Experience designing or supporting AI/ML systems in production is a strong plus
• Comfort working on infrastructure, data pipelines, and evolving system architectures
• Strong communication skills and the ability to collaborate in a high-ownership environment
• Experience working in a startup or fast-moving product organization
• Willingness to travel occasionally to customer sites to understand real-world constraints
• Working experience in FinTech, quantitative analysis, and econometrics greatly preferred

• A robust selection of health, dental, and vision insurance options
• Unlimited PTO with a three week minimum per year, plus additional sick days
• Top of the line work equipment and IT setup, including high performance laptops and a modern developer stack
• Unlimited access to the latest AI agent systems and productivity tools to help you move faster and build better
• Visa support for candidates currently based in the US, including employer sponsored visa applications where applicable
• The anticipated base salary range for this role is $132,000 to $150,000.
• This role sits at the intersection of AI systems, time-series data, and real-world energy infrastructure. Your work will directly impact system reliability, customer trust, and CVector's ability to scale intelligent energy management across industries.
• If you enjoy solving deep backend problems, shaping platform foundations, and embedding intelligence into physical systems, this role offers both technical challenge and real-world impact.