• Own production reliability and availability targets • Drive security remediatio • Build incident response process with root cause analysis • Implement SLOs/SLIs for core services • Operate edge protection (Cloudflare WAF, rate limiting, DDoS, Bot Management) • Improve CI/CD and test environments for development teams • Establish CI/CD security practices • Expand Infrastructure as Code coverage • Lead and develop the DevOps engineer on your team

Role Description We are looking for a DevOps Engineer to own and evolve the cloud infrastructure that powers our computational biology platforms, internal applications, and data pipelines. You will build and maintain systems spanning workflow orchestration for genomics and structural biology workloads, internal-facing scientific applications, and the security and reliability infrastructure that supports them. This role sits at the intersection of cloud engineering, scientific computing, and applied software development. You will work closely with computational biology, antibody discovery, and software engineering teams to translate prototype workflows into production systems, ensure uptime and observability for the tools scientists rely on daily, and apply security best practices appropriate for a biotech environment handling sensitive scientific and business data. This role is 100% remote and can be based in the US, Canada, Mexico, Central America, or South America. Key Responsibilities - Architect, deploy, and maintain cloud infrastructure across Google Cloud Platform (primary) and AWS (secondary), focusing on cost efficiency, reproducibility, and security across compute, storage, networking, and identity. - Manage infrastructure-as-code using Terraform, with full version control via GitHub and CI/CD pipelines that support both scientific compute and internal application deployment. - Support and extend our scientific compute infrastructure, including Cromwell, Google Batch, Cloud Run, Cloud Storage, and GPU-accelerated environments for protein design, structural prediction, and machine learning workloads. - Maintain uptime, observability, and incident response for internal applications including Slack integrations, web dashboards, and data ingestion services that connect lab and computational workflows. - Implement and uphold data security practices appropriate for a biotech environment, including IAM, secrets management, audit logging, network segmentation, and compliance-adjacent controls. - Collaborate with computational biologists and software engineers to operationalize new tools and pipelines, translating prototype workflows into reliable production systems. - Triage and resolve infrastructure issues across the stack, with clear documentation and post-mortems that improve the system over time. - Articulate technical decisions and trade-offs to diverse audiences, including engineering and scientific teams. Qualifications - DevOps Engineer: 4+ years of hands-on DevOps, SRE, or cloud infrastructure experience. - Strong production experience with Google Cloud Platform (GCE, GKE, GCS, Cloud Run, IAM, Cloud Logging, Batch) and working knowledge of AWS (EC2, S3, IAM, Lambda). - Deep proficiency with Terraform, GitHub Actions or equivalent CI/CD systems, and Docker. - Proficiency in Python for scripting, automation, and data handling; comfortable in Unix or Linux terminal environments. - Practical experience implementing data security controls, including encryption, access policies, secrets management, and audit trails. - Demonstrated ability to maintain internal-facing applications and services with high uptime expectations. - Excellent written and verbal communication in English, with the ability to document systems clearly for both engineers and scientists. - Working hours that include meaningful synchronous overlap with US Pacific Time. Preferred Qualifications - Fluency with AI-augmented development workflows, including practical use of tools such as Claude Code, Cursor, or GitHub Copilot as part of day-to-day infrastructure and scripting work. - Experience supporting scientific or research computing environments (genomics, single-cell, structural biology, ML, or HPC). - Familiarity with workflow orchestration systems such as Cromwell, Nextflow, WDL, or Airflow. - Experience with GPU infrastructure and scheduling of ML or protein design workloads. - Background in life sciences infrastructure, including familiarity with Benchling, ELN integrations, or scientific data management systems. - Prior experience at an early-stage biotech, scientific software company, or research-driven startup. - Familiarity with SOC 2, HIPAA-adjacent, or other regulated-environment security frameworks. Logistics - Fully remote, open to candidates based in the Americas (US, Canada, Mexico, Central America, or South America). - You will report directly to the head of computational biology. - Compensation calibrated to local market with US benchmarking. - Direct collaboration with our US-based engineering and computational biology teams in South San Francisco.

Role Description This role will be responsible for all operational database administration duties, data engineering, and data operations within the Data Lake and Enterprise Data Warehouse (Snowflake) ecosystem including, but not limited, to the following: - Take the lead on our daily database administration, ensuring our data environment stays healthy and reliable. - Partner closely with our Staff EDW Architect to bring new visions to life, designing high-quality data artifacts that follow industry best practices. - Turn business needs into smart, reusable ETL solutions that grow alongside our company. - Design end-to-end pipelines using your expertise with data models and architecture diagrams to build automated ingestion and transformation pipelines that keep our data moving on schedule. - Analyze and produce artifacts such as Source-to-Target Mapping documents. - Build pipelines that bring together data from everywhere—whether it’s RDBMS, APIs, JSON, or flat files—creating a seamless flow of information. - Define the "Source of Truth" using tools like Python and ETL software to clean, integrate, and transform data into a single, reliable resource the whole company can trust. - Provide day-to-day operational support for all the data pipelines by monitoring and investigating alerts, while troubleshooting and remediating production issues in a timely manner. - Act as a player-coach for junior and intermediate data engineers and ETL developers as the EDO team grows. Qualifications - Deep experience performing ETL design and development via custom coding (SQL, Python, Spark, Java, etc.) as well as using ETL tools (e.g., Coalesce, Informatica, DataStage, Talend) and other tools such as Data Quality tools, Metadata Manager, etc. - Extensive hands-on, professional experience working with Snowflake as a Database Administrator (DBA) and clear understanding of Snowflake’s Access Control framework. - Comfortable with Cloud-hosted solutions, especially AWS with experience deploying Secrets Manager, KMS, S3, EC2, Linux, Cross-Account Access, etc. in a scaled environment. - Innate curiosity to fundamentally understand and solve problems. - Understanding of data warehousing architecture fundamentals (e.g., Kimball vs. Inmon, Medallion Architecture, 3NF data models, reference data models, dimensional models, conformed dimensions, SCDs, etc.). - Experience in orchestrating data operations via tools such as Apache Airflow, Cron, Astronomer, etc. Requirements - The compensation range listed for this role reflects the expected hourly rate for candidates located in Ontario, Canada. - This range represents hourly rate only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package. - Factors Influencing Final Compensation: - The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate's specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications. - Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer. - Ontario Hourly Band: $100,000 — $125,000 CAD Benefits - Highly competitive salary - Retirement/401K/Pension Savings globally - Competitive Paid time off packages including birthdays off! - Access to a comprehensive mental health care program - Health benefits from day one of employment - Work from home reimbursements - Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto - Robust training and onboarding program - Coverage and support of personal development initiatives (conferences, courses, books, etc.) - Access to StackAdapt programmatic courses and certifications to support continuous learning - An awesome parental leave program - A friendly, welcoming, and supportive culture - Our social and team events!

• Building and/or migrating virtualized environments • Automating and orchestrating deployment of virtualized solutions in private cloud • Working in agile methodology and collaborating with the rest of the team • Mentoring teammates and sharing knowledge