QA Engineer

Prudentia Sciences•Cambridge, MA
•$120,000 - $145,000•Hybrid

About The Position

Prudentia Sciences is hiring its first dedicated QA Engineer to build quality into its AI-powered platform for biopharma, biotech, and life sciences investors. This hands-on engineer will write code and build quality practices from the ground up, with a focus on correctness, performance, and reliability. The role partners closely with engineering, product, and machine learning teams to protect customer trust and support the company’s growth. The QA Engineer will create and maintain automated UI, API, and data-pipeline tests; integrate testing into CI/CD quality gates; track and triage defects; and validate ML-driven outputs as they move into user-facing views. The role also supports performance, reliability, security, and sensitive-data testing, while helping translate scientific and business needs into testable acceptance criteria and fostering a quality-first culture.

Requirements

  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
  • Proven experience testing modern web applications and building automated test suites.
  • Hands-on experience with automated testing frameworks such as Playwright or Cypress, and API testing tools such as pytest, REST-assured, or pactflow.
  • Experience integrating automated tests into CI/CD pipelines, such as GitHub Actions, and establishing quality gates.
  • Comfort reading code and working with engineers to understand system architecture, APIs, and data flows well enough to design meaningful tests.
  • Experience testing applications with complex, data-driven workflows.
  • Skill in writing clear, reproducible bug reports and test plans, and familiarity with issue trackers such as Jira or Linear.
  • Strong problem-solving skills and an analytical mindset.
  • Meticulous attention to detail and a genuine passion for quality.
  • Autonomous, self-starter attitude with a strong sense of ownership.
  • Excellent communication skills, including the ability to explain technical issues clearly to non-technical audiences.
  • Strong collaboration skills and the ability to work with engineers, product managers, and scientific domain experts.

Nice To Haves

  • Familiarity with secure data-handling practices and testing in regulated or sensitive-data environments, especially healthcare, life sciences, or enterprise environments.
  • Passion for continuous learning and improving testing practices as the platform evolves.
  • Interest in building products that have meaningful impact.

Responsibilities

  • Build and maintain automated UI, API, and data-pipeline test suites to support fast, confident releases.
  • Use AI coding tools, such as Claude Code, to build and maintain tests, while critically reviewing their output.
  • Partner with engineering to integrate automated tests into CI/CD pipelines and establish quality gates before staging and production.
  • Eliminate flaky or long-running tests from CI quality gates.
  • Identify, document, and triage defects with clear reproduction steps; coordinate prioritization and verify fixes.
  • Validate the accuracy and consistency of ML-driven risk analyses, valuations, and scientific assessments as they move from the orchestration layer into user-facing views.
  • Support load, performance, and reliability testing to meet availability and responsiveness expectations.
  • Help verify secure handling of sensitive scientific and deal data and support testing aligned with healthcare and life sciences data best practices.
  • Work with engineers, product leads, and domain experts to translate scientific and business requirements into testable acceptance criteria.
  • Advocate for testability in design reviews, improve test coverage, and stay current on modern QA tools and practices.

Benefits

  • Competitive salary and equity.
  • Opportunity to build and lead the platform as a foundational engineering leader.
  • Opportunity to shape the product experience during a critical scaling phase.
  • Collaborative, mission-driven colleagues.
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