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Prudentia Sciences

AI-driven life sciences due diligence platform

Quality Engineer - Software Development Engineer in Test

Test Automation EngineeringUpdated on Nov 9
Full-time

About the Job

Requirements

  • A bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
  • Proven experience testing modern web applications and designing and building automated test suites, ideally as the person who owned them.
  • Hands-on experience with automated testing frameworks such as Playwright or Cypress and API testing tools such as pytest, REST-assured, or pactflow.
  • Experience owning automated tests in CI/CD pipelines such as GitHub Actions, including setting up quality gates and managing flaky tests.
  • Hands-on daily use of AI coding tools such as Claude Code, Cursor, or Copilot, with a habit of verifying their output.
  • Experience designing load or performance tests and identifying real bottlenecks.
  • Comfort reading code and working directly 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 explaining quality risks and release readiness to the team.
  • Familiarity with secure data-handling best practices and testing in regulated or sensitive-data environments.
  • Ability to work closely with engineers, product managers, and scientific domain experts to deliver a high-quality user experience.

Responsibilities

  • Design, build, and maintain automated test suites across UI, API, and data pipelines, with most coverage at the API and data layers, to support fast, confident shipping as the platform scales.
  • Use AI coding tools such as Claude Code daily to build and maintain tests, verify their output, and keep sensitive data out of AI tools.
  • Own automated quality gates in CI/CD pipelines such as GitHub Actions, decide what blocks a release, and eliminate flaky or long-running tests.
  • Test at the API layer by default and catch breaking changes between services before they reach production.
  • Own load, performance, and reliability testing so the platform meets availability and responsiveness expectations while handling large volumes of sensitive, time-sensitive data.
  • Identify, document, and triage defects with clear reproduction steps, work with engineers to prioritize fixes, and make go/no-go release calls.
  • Validate the accuracy and consistency of ML-driven outputs, including risk analyses, valuations, and scientific assessments, as they move from the orchestration layer into user-facing views.
  • Help verify secure handling of sensitive scientific and deal data, including keeping each customer's data separate.
  • Work cross-functionally with engineers, product leads, and domain experts to translate scientific and business requirements into clear, testable acceptance criteria.
  • Advocate for testability in design reviews, improve test coverage over time, and stay current on modern QA tooling and practices.

About the Company

Prudentia Sciences

AI-driven life sciences due diligence platform

Prudentia Sciences provides an AI-native platform for due diligence and dealmaking in the life sciences sector, serving biopharma, biotech, and financial buyers such as venture capital and private equity firms. The platform merges artificial intelligence (including large language models and deep learning) with scientific expertise and financial modeling to speed asset evaluation, offering rapid data-room synthesis, real-time valuation simulations, and scenario planning with a human-in-the-loop for expert input. It differentiates itself by tightly integrating AI analytics with domain knowledge and financial modeling to identify risks and optimize trade-offs across time, cost, probability of success, and revenue, enabling faster go/no-go decisions. Its goal is to de-risk investments, shorten deal cycles, and scale the platform globally, expanding into Asia-Pacific and Europe with backing from seed and Series A funding led by GV, Iaso Ventures, Virtue, and McKesson Ventures.

Company size
11-50
Company stage
Series A
Total funding
$27M
Headquarters
Cambridge, MA
Founded
2023

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