Senior Software Engineer - Study Lifecycle Tooling - Evinova

WHY JOIN US?

Evinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone.

Operating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide.

At Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment.

We also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection.

This role is located in Gaithersburg, Maryland. Candidates must reside within commuting distance of Gaithersburg or be willing to relocate for this opportunity.

About the Role

We are looking for a Senior Software Engineer to help design, build, and evolve the backend services and APIs that enable clinical trial teams to configure, deploy, and maintain digital study experiences.

You will develop business-critical software that helps global clinical trial teams configure studies, manage changes, and operate digital study experiences safely and efficiently. This is a hands-on, primarily backend-focused role with significant product impact.

You will own technical outcomes, contribute to technical design and engineering decisions, and collaborate with engineers, UX designers, product colleagues, and study delivery teams to solve complex problems across the study lifecycle.

The team is distributed. You will work alongside colleagues based in Gaithersburg and with teammates in other locations and time zones, including Europe. In practice this means some early-morning overlap with European colleagues, and a need to be flexible and deliberate about how you coordinate, communicate, and document decisions across locations.

We expect engineers to use approved AI tools responsibly in their development workflow. You remain accountable for reviewing and validating AI-generated output and for meeting security, privacy, quality, and regulatory requirements.

What you will do

• Build software: Design, develop, and maintain reliable tools for study configuration, deployment, operation, and maintenance.

• Develop backend services: Build TypeScript and Node.js services, REST APIs, integrations, and data models.

• Contribute to technical design: Evaluate technical options and trade-offs and contribute to reusable engineering patterns and standards.

• Own technical outcomes: Take significant features, services, or technical initiatives from design through implementation, testing, deployment, and ongoing improvement.

• Collaborate across locations: Work with engineers, UX designers, product colleagues, and study delivery teams — locally and across time zones — to turn complex problems into practical solutions, keeping decisions transparent and well documented for colleagues who are not online at the same time.

• Build quality and security in: Develop clean, maintainable, testable, and secure software with appropriate automated testing.

• Support reliable systems: Design for scalability, observability, resilience, and performance, and contribute to monitoring, troubleshooting, and release support in line with the team’s production-support model.

• Improve the team and platform: Reduce technical debt, strengthen automation, share knowledge, mentor colleagues, and improve engineering practices.

What success looks like

Success in this role means delivering reliable capabilities that make study setup and maintenance simpler, safer, and more scalable. In your first year, you will:

• Ship capabilities study teams rely on: Deliver features that measurably reduce the manual steps and rework involved in setting up and maintaining a study.

• Cut time to configure a study: Remove friction from configuration and change workflows so study teams reach a working setup faster and with fewer errors.

• Raise the platform’s reliability bar: Improve test coverage, observability, and incident response for the services you own, so regressions are caught before release.

• Establish reusable patterns: Create technical approaches and documentation that other squads can adopt, while helping colleagues grow through mentoring and code review.

About you

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