Full-Time

Member of Technical Staff Staff Engineer

Collinear AI

Collinear AI

1-10 employees

Simulated labs for enterprise AI testing

Compensation Overview

$200k - $400k/yr

+ Equity + Bonus

San Francisco, CA, USA + 2 more

More locations: Sunnyvale, CA, USA | United States

Hybrid

Hybrid work is required in Sunnyvale or San Francisco, California.

Category
Software Engineering (1)
Required Skills
Kubernetes
Microsoft Azure
Python
Distributed Systems
Data Engineering
Docker
AWS
Google Cloud Platform

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Requirements
  • Seven to ten or more years of experience building backend systems, platforms, or cloud services.
  • Strong experience with distributed systems, infrastructure, and cloud-native architectures.
  • Hands-on experience with Python as the primary language, Docker, Kubernetes, and at least one of AWS, Google Cloud Platform, or Microsoft Azure.
  • Experience building or operating B2B software-as-a-service platforms at scale, including multitenancy and reliability concerns.
  • Experience working directly with customers in a B2B setting, including handling escalations and ambiguous requirements.
  • Strong communication skills and sound technical judgment.
Responsibilities
  • Own the architecture, reliability, and scalability of the company’s AI agent improvement product offerings.
  • Design and operate multi-tenant, distributed backend systems that support enterprise customers.
  • Make platform-level decisions across infrastructure, runtimes, deployment models, and developer experience.
  • Translate customer needs and ambiguity into clear engineering priorities and durable platform capabilities.
  • Partner with founders and research leadership on technical strategy, roadmap, and tradeoffs.
  • Establish engineering standards and best practices as the platform and team scale.
  • Hire and mentor engineers over time as the organization grows.
Desired Qualifications
  • Experience in cloud or data infrastructure companies such as AWS, Google Cloud Platform, Microsoft Azure, Databricks, Snowflake, Datadog, or Confluent.
  • Prior experience at an early-stage startup.
  • Some people-management or hiring experience.
  • Experience working on machine-learning platforms, evaluation systems, or large-scale data pipelines.

Collinear AI builds simulation labs where AI agents learn enterprise work before going to production. The labs provide realistic enterprise environments: enterprise APIs, users who push back and change their minds, tasks with real-world ambiguity, and verifiers that score what actually matters. This lets teams stress-test AI agents and continuously improve them after deployment. Collinear AI collaborates with frontier AI labs and large enterprise AI teams such as ServiceNow, IBM, HUMAIN, and Zoho. Their goal is to help organizations verify and improve AI agents in reproduceable, controlled settings before they are used in production.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

Mountain View, California

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • ServiceNow, MasterClass, Amazon, and Matillion case studies validate enterprise demand in 2025-2026.
  • Google Cloud Marketplace launch on August 25, 2025 expands buyer access and credibility.
  • Hiring in Sunnyvale, Bengaluru, and Mountain View signals active product and research expansion.

What critics are saying

  • OpenAI, Google, and Anthropic bundle adjacent evaluation tools, compressing Collinear's pricing power.
  • Collinear relies on enterprise trust; one major safety failure destroys its core value proposition.
  • No disclosed funding since 2021 leaves runway and scale uncertain against better-capitalized rivals.

What makes Collinear AI unique

  • Simulation Lab creates realistic sandboxes for agents before production deployment.
  • Proprietary judges and verifiers generate grounded reward signals and automated red-team testing.
  • Google Cloud Marketplace availability broadens enterprise distribution beyond direct sales.

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Benefits

Company Equity

Performance Bonus