Scientific Solutions Engineer

Seqera is a leading bioinformatics platform that seamlessly integrates data, pipelines, and teams, empowering scientists to accelerate research and development.

Seqera

Employee count: 51-200

CA, ES + 1 more

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Seqera exists to advance science for everyone through software. We provide software for scientists solving today's most complex and important challenges.

Requirements

Master's or PhD in Bioinformatics, Computational Biology, or a related field.
1–3 years of relevant industry experience in a technical pre-sales, services, or bioinformatics role.
2-3 years of hands-on experience with Nextflow.
Experience with cloud (AWS, GCP, Azure) or HPC environments.
Proficiency with Linux/Unix and at least one programming language (Python, R, etc.).
Knowledge of containerization (Docker/Singularity) and version control (Git).
Strong problem-solving skills and attention to detail.
Collaborative mindset and interest in cross-functional teamwork.
Self-motivated, adaptable, and eager to learn in a fast-paced environment.

Benefits

Opportunity to work with a company with a bigger purpose

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About the job

Apply before

Jun 30, 2026

Posted on

May 01, 2026

Hiring timezones

United States +/- 0 hours, and 2 other timezones

Job categories

Technical Solutions Engineer Solutions Engineering Jobs Solutions Engineer Data Solutions Engineer Clinical Solutions Engineer Solutions Application Engineer Solution Engineer

Skills

Nextflow Linux Unix Python R Docker Singularity Git Bioinformatics Computational Biology

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About Seqera

Learn more about Seqera and their company culture.

View company profile

Build, Deploy & Scale Your Science. From Discovery to Impact. The bioinformatics platform that brings your data, pipelines, and teams together—from the developers of Nextflow.

Seqera centralizes data, streamlines pipelines, and brings mission-critical infrastructure under one secure, compliant umbrella. Your Data. Your Infrastructure. Your Science. Integrate Seqera into existing on-premises systems and cloud platforms like AWS, GCP, and Azure—with no forced migrations. Maintain full control over data residency and scale globally, without compromising security or performance. Optimize every workload, from large-scale genomics to advanced AI-based drug discovery.