Top Biotech DevOps & Platform Engineering Jobs

The Principal Cloud and Infrastructure Engineer leads Azure-centric cloud environments integration with AWS and on-prem infrastructure, focusing on scalability, automation, and compliance.

Lead and own Mirum's Salesforce Life Sciences Cloud platform for Patient CRM and HCP Portal. Drive post-go-live stabilization, platform governance, integrations, support models, stakeholder prioritization, and continuous improvement to ensure scalable, compliant operations.

Manage and maintain core IT systems, endpoints, servers, and networking; troubleshoot incidents across locations; deploy and manage MDM and workstations; support cloud migrations, security upgrades, and documentation; partner with labs and vendors to ensure reliable operations.

As a Senior Platform Engineer, you will design and maintain AWS infrastructure, develop backend services, automate deployments, and ensure platform reliability while collaborating with engineering teams.

Design, manage, and support Microsoft Server and VMware environments, storage (SAN/NAS), and Backoffice services. Ensure high availability, security, patching, disaster recovery, capacity planning, documentation, and provide tier‑3/on‑call support across multiple locations. Collaborate with clinical staff and vendors and drive technology improvements.

The Senior IT Systems Engineer will oversee cloud infrastructure reliability, security, performance, and systems administration across various platforms, ensuring effective and efficient IT operations.

The Senior Linux Systems Engineer will design and maintain high-performance Linux systems, optimize performance, automate tasks, and ensure system reliability. Responsibilities include troubleshooting, collaboration, and documentation.

Lead and supervise installed low code application systems, configure operating systems, implement architecture, and provide DevOps support to teams.

Lead the platform engineering team to enhance software delivery for sequencing systems, overseeing infrastructure, CI/CD pipelines, and collaborating across departments for quality and efficiency.

You will design and optimize distributed compute infrastructure for ML applications, improve resource utilization, and collaborate with ML engineers on large-scale workloads.