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Senior Software Engineer in Test – AI & Quality Infrastructure at Vast Data · Trevo
The Reality
Most QA roles are about writing scripts to catch bugs after the code is written. This isn't one of those roles.
At VAST Data, we aren't just scaling software; we are building the fundamental engine that powers the global AI revolution. When you are managing exabytes of data at breaking-point speeds, traditional testing methodologies crumble. We don't need someone to follow a test plan. We need an architect to build a self-evolving, intelligent testing ecosystem.
The Mission
We want you to build the AI tools that validate our AI data platform. You will design autonomous, agentic systems that actively look for vulnerabilities, orchestrate their own testing logic, navigate distributed dependencies, and isolate regressions entirely on their own before they hit production.
If you are a systems-level builder who gets excited by complex distributed systems, autonomous logic, and breaking things at an elite engineering scale, this is your playground.
Requirements
What You’ll Actually Do Everyday
Build AI Agents for Quality: Design and deploy production-grade Python frameworks and LLM-driven agentic tools that dynamically generate, execute, and self-correct test environments.
Orchestrate Chaos at Scale: Move past static assertions. You’ll build runtime verification tools that stress-test data integrity, multi-node failures, and deep storage engine behaviors.
Ditch the Manual Mindset: Drive our entire automation architecture toward a state where human intervention is the exception, not the rule.
Partner with Core R&D: Work side-by-side with our systems architects to inject intelligent code evaluation pipelines right into our fast-moving CI/CD engines.
A Builder's Mindset: You consider yourself a software engineer first, who happens to apply their skills to infrastructure reliability and complex validation.
Python Mastery: You don't just use automation tools; you build them. You write clean, scalable, object-oriented code that other engineers love to read.
Distributed Systems Context: You understand the unique pain points of Linux kernels, multi-tenant networking layers, containerization (Docker/K8s), and data pipeline architectures.
AI Curiosity: You have hands-on experience or deep curiosity regarding LLMs, prompt pipelines, and modern AI developer environments.