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Senior Quality Engineer

Domino Data Lab

full-remoteseniorpermanentqa Full remote - New York, US 8 days ago via WTTJ

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Tags

Quality EngineeringTest AutomationCI/CDKubernetesAWSAzureGCPMLOpsLLM-Assisted TestingContract Testing

About the role

Role Overview

Join Domino Data Lab’s Quality Engineering team as a Senior Quality Engineer. You’ll help raise the quality bar across the engineering organization by building scalable testing and automation practices that enable fast, reliable software delivery.

Key Responsibilities

  • Extend and harden the automation framework to cover under-tested areas and support higher-velocity merges.
  • Increase automated test coverage on critical paths, targeting 100%, while maintaining quality as merge velocity grows.
  • Build an LLM-assisted test pipeline to align AI-accelerated development with AI-accelerated testing.
  • Drive customer-reported defects toward zero.
  • Make quality posture visible to leadership through reporting and measurable quality metrics.

Profile / Requirements

  • Owned a complex automation platform, including end-to-end frameworks, CI systems, and multi-stage automation.
  • Shipped compliance-critical software where correctness impacted customer audits (e.g., audit trail, RBAC, governance correctness).
  • Senior-level influence across multiple teams without direct authority.
  • Strong Kubernetes and cloud-native fluency at scale, including AWS, Azure, and/or GCP.
  • Background in MLOps or data-platform domains (e.g., model registries, lineage, MLflow, data lake/warehouse).
  • LLM-augmented QA experience (test generation, triage, or fuzzing with AI).
  • Experience with stateful workflow / approval-flow testing (state machines, gated transitions, policy engines).
  • Experience with contract testing for integration-heavy products with connector/plugin matrices.

Nice to Haves

  • Knowledge of the cucu library.
  • Scala or Go.

About Domino Data Lab

Domino Data Lab is a company focused on data science and MLOps tooling, helping teams build, deploy, and manage machine learning workflows. The company operates in domains such as pharma, finance, government tech, and health tech, where software reliability and governance are critical.

Scraped 6/11/2026

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