Key skills
PythonShellBashPytestKubernetesDockerGitHub ActionsHelmPodmanPostgresSQLiteGitGitHubCI/CD
About this role
RapidFort is the leader in end-to-end software supply chain security. They are seeking a hands-on Sr. QA Automation Engineer to own and evolve the Python-based test automation framework for their CLI-driven security platform, focusing on test reliability and automation of security workflows.
Responsibilities:
- Build and maintain robust automation suites using Python and pytest
- Convert manual/bash test plans into scalable, data-driven test frameworks (CSV/JSON/YAML)
- Design selective execution strategy (tags, ranges, run flags, grouping/sharding)
- Automate CLI command validation (exit codes, stdout/stderr expectations, failure semantics)
- Integrate and maintain test execution in CI/CD pipelines (GitHub Actions or equivalent)
- Validate container image hardening, scan outputs, and SBOM/RBOM generation across base distributions (Ubuntu, RHEL, Debian, Alpine)
- Manage and improve test artifacts/reporting (.html, .log, .json) for fast triage
- Troubleshoot environment/auth/configuration drift across runners and VMs
- Maintain high-quality handover docs, runbooks, and troubleshooting guides
- Partner with dev/platform teams to stabilize flaky tests and shorten feedback loops
Requirements:
- 10+ years in SDET or QA Automation roles
- 5+ years of Python automation experience (pytest required)
- Strong Linux and shell scripting (bash) skills
- Hands-on experience testing CLI tools or developer workflows
- Experience with Docker and/or Podman
- Experience integrating and debugging test runs in CI pipelines
- Strong debugging skills for authentication, environment, and infra-related failures
- Solid Git workflow and code review practices
- Kubernetes/KIND/Helm testing experience
- Compliance/security scan automation exposure (SBOM/STIG-like workflows)
- Multi-runner parallel execution/sharding strategy experience
- Experience capturing test telemetry for trend analysis (Postgres/SQLite)
- Experience building reusable reporting and observability layers