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TensorStax

Backend Engineer, Data & Agent Platform

San Francisco, CA
Python API Go Spark Airflow dbt Kafka
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Description

Backend Engineer, Data & Agent Platform

Location: San Francisco, CA

Department: Engineering

Location Type: IN_OFFICE

Employment Type: FULL_TIME

Backend Engineer – Data & Agent Platform
Location: San Francisco (Hybrid)

About TensorStax
TensorStax is building fully autonomous AI systems to manage and optimize mission-critical data infrastructure. Our platform integrates agentic AI capabilities with large-scale data systems, enabling intelligent orchestration, automated pipeline management, and self-healing infrastructure.

We are looking for a Backend Engineer to help build the core agent framework powering TensorStax and integrations into popular data engineering tools.

What We’re Looking For:

  • Strong software engineering experience in Python, with a focus on performance, reliability, and distributed systems.
  • Hands-on experience building agentic AI applications, especially in domains such as computer control or code gen.
  • Track record of contributions to open-source agentic frameworks such as LangChain, AutoGen, etc.
  • Deep understanding of distributed systems, API design, and backend architectures.
  • High agency—ability to take ownership, navigate ambiguity, and independently push projects forward.
  • Former founders or engineers who have built and owned significant technical projects are highly valued.

Bonus Points:

  • Experience with GoLang for high-performance backend services.
  • Strong understanding of big data transformation, ETL, and ELT pipelines.
  • Proficiency in Spark, Airflow, dbt, Kafka or other data engineering tools.
  • Familiarity with streaming architectures, event-driven systems, and async processing.
  • Experience optimizing large-scale data pipelines for performance and cost efficiency.

Benefits:

  • 100% employer-covered health, dental, and vision insurance.
  • 401(k) with company match.
  • Access to Bay Club or Equinox in San Francisco.

TensorStax
TensorStax

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