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# Software Engineer - Backend & AI Infra focus

- **Company:** Capital Vacuum Floor-Care World, LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $132,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Databases, Data Infrastructure, Programming Tools, Github, Python (Programming Language), PostgreSQL, Message Broker, Message Queuing Telemetry Transport (MQTT), Node.Js, Data Streaming, TypeScript, Parquet, Data Ingestion, Backend, Event Driven Architecture, AI Platforms, Information Technology, Influxdb, Data Analytics, Graphql, Machine Learning Operations, Front End Software Development, Api Design, Data Pipelines, Service Stack
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-backend-ai-infra-cvector-industrial-ai-8301984

## About the Role

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

## Description

As a Senior Software Engineer - Backend & AI Infra focus, you will play a critical role in evolving CVector's core backend platform. You will work on time-series data systems, AI-assisted analytics, cloud infrastructure, and data ingestion pipelines that power our customer-facing applications and internal modeling platforms.

This role is well-suited for an engineer who enjoys working close to the data and infrastructure layers, has strong architectural judgment, and is excited to operate across AI systems, databases, and distributed backend services. You will take ownership of complex systems, drive major technical migrations, and help shape how intelligence is embedded into industrial energy workflows.

You will collaborate closely with product, modeling, and frontend engineers, and you will have significant influence over platform direction, reliability, and long-term scalability., 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

Backend Platform & Data Infrastructure

 * 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

Database & Analytics Systems

 * 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

Modeling Platform Support

 * Improve and consolidate internal machine learning systems
 * 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

Reliability & Developer Experience

 * 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


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