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AI Test Coverage Optimization Engineer

Lillian Nguyen

Full-time · Job · Los_Angeles

About the role

Our platform generates synthetic test data and AI-powered test cases for software QA teams. We have 1,100 clients using it, and the most common feedback is: I don't know if my test suite actually covers the risky parts of my codebase. Test coverage percentages are easy to game — they tell you which lines ran, not whether the tests catch real bugs. You'll work on the coverage intelligence layer: analyzing code structure and change history to identify under-tested paths, prioritizing test generation toward high-risk areas, and building the dashboards that show QA leads where their coverage gaps actually are. The work involves code analysis (AST parsing, dependency graphs), ML-based risk scoring, and visualization. This is a junior role with genuine learning opportunities. Our senior engineers have backgrounds in compilers, program analysis, and distributed testing infrastructure. You'll work closely with them on a problem that sits at the intersection of software engineering and ML.

Responsibilities

  • Build code analysis pipelines using AST parsing and dependency graph extraction
  • Develop risk scoring models that identify under-tested high-change code paths
  • Create dashboards visualizing coverage gaps and test prioritization recommendations
  • Maintain integrations with GitHub, GitLab, and common CI/CD platforms
  • Write tests for the coverage analysis system itself
  • Contribute to documentation on coverage methodology for client-facing materials

Requirements

  • 1+ year of professional Python development
  • Basic understanding of software testing concepts and code coverage metrics
  • Familiarity with Git and CI/CD pipelines
  • Curiosity about compilers, program analysis, or software reliability
  • Ability to learn quickly in a technically deep environment

Benefits

  • Fully remote with flexible schedule
  • Health and dental coverage
  • $1,500 learning stipend
  • Mentorship from senior engineers
  • Structured growth path

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Categories

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python docker sql fastapi aws

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

Under $60k / year

AI Expertise

Automation & AI Workflows MLOps & AI Infrastructure

Skills

python docker sql fastapi aws

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