About us
Founded in 2018, Causaly accelerates how humans acquire knowledge and develop insights in Biomedicine. Our production-grade generative AI platform for research insights and knowledge automation enables thousands of scientists to discover evidence from millions of academic publications, clinical trials, regulatory documents, patents and other data sources… in minutes.
We work with some of the world's largest biopharma companies and institutions on use cases spanning Drug Discovery, Safety and Competitive Intelligence. You can read more about how we accelerate knowledge acquisition and improve decision making in our blog posts here: Blog - Causaly
We are backed by top VCs including ICONIQ, Index Ventures, Pentech and Marathon.
About the role:
The Senior DevOps Engineer will work on building, scaling and automating our infrastructure and platform. The DevOps team manages infrastructure in all 3 major cloud vendors and candidates are expected to work in all 3. Please note that we are unable to sponsor visas for this position.
Responsibilities:
- Designing, creating and maintaining the infrastructure for Causaly Cloud products.
- Work with stakeholders across multiple teams to design, build and continuously improve the infrastructure.
- Provide support for high-level application issues.
- Work on a variety of tasks related to our platform.
- Scaling and automating new and existing components.
- Manage the infrastructure to handle volumes of data in various formats, e.g. comma-separated, json, relational, graph database formats etc.
Minimum Qualifications:
- BSc in a related technical field or equivalent practical experience.
- Experience with multiple cloud providers.
- Excellent knowledge of Terraform.
- Excellent knowledge of Linux environments including scripting (Bash and Python).
Preferred qualifications:
- Experience with container technologies and automation tools.
- Good knowledge of cloud architecture and best-practices.
- Experience with monitoring tools (e.g. Datadog)
- Previous experience working in a startup and able to adapt to new/changing requirements.
- Support security related tasks (e.g. implementing/running internal scans).
- Supporting ElasticSearch clusters.
- Experience with data warehouses, pipelines and data engineering for large datasets.
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