Senior Software Engineer - Backend & AI Infra

Key Responsibilities

• Contribute across several interconnected areas: Intelligent Systems, Backend Platform & Data Infrastructure, Database & Analytics Systems, and Reliability & Developer Experience.
• 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.
• Refined 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.
• Optimize performance and reliability of high-volume time-series data stores.
• 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.
• Augment analytical workloads using Parquet and/or Iceberg-based storage formats.
• Balance real-time and historical query performance across operational and analytical use cases.
• Improve and consolidate internal machine learning systems.
• 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.

Requirements

• 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.
• Familiarity with databases, especially PostgreSQL and time-series or analytical data stores.
• Experience 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.

Benefits

• A competitive compensation package with meaningful equity upside.
• Robust selection of health, dental, and vision insurance options.
• Optional Health Flexible Spending Account (FSA).
• 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.

Why This Role Matters at CVector

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.