What are the responsibilities and job description for the Senior DevOps Engineer position at GenBio AI?
In this dynamic and innovative environment, you'll lead a team of 2-3 members in our 3 offices as a start, collaborating with engineers, scientists, and machine learning researchers to develop a platform that enhances productivity organization-wide. Your role includes establishing standards and shaping the developer experience throughout the company.As we are in the early stages of our journey, with ongoing learning and some ambiguity, your prior experience and proactive approach will be essential in defining your impact in this newly established position.
Responsibilities
You will continue to develop and empower a diverse team of developers, providing technical guidance and direction and anticipating future resource needs in line with business goals and priorities
Develop and implement a scalable technical strategy to address complex challenges.
Establish technical standards and enhance the developer experience across the organization.
Define team goals, drive execution, and manage cloud infrastructure (GCP, Docker, Terraform, etc.).
Develop reliability and observability strategies to ensure system performance and resilience.
Build tools and processes for effective operational and software development management.
Collaborate on team strategy, set goals, and provide technical direction while fostering growth.
Partner with cross-functional teams (science, engineers, and operations) to align initiatives.
Contribute to core decisions on tools, infrastructure, and architectural design.
Build and operate processes and tools for effective operational management of research and production software and to enable and enhance effective software development practices.
Qualifications
Cloud Infrastructure : Proven experience in building, deploying, and maintaining production systems on major cloud platforms, with a preference for Google Cloud Platform (GCP).
Containerization and Orchestration : Proficiency with Docker and Kubernetes / KubefLow for containerization and orchestration, ensuring efficient deployment and scaling of applications.
Infrastructure as Code (IaC) : Strong understanding of IaC principles, utilizing tools like Terraform to manage and provision cloud resources.
Continuous Integration / Continuous Deployment (CI / CD) : Experience with CI / CD pipelines and release management, employing tools such as GitLab CI, GitHub Actions, or CircleCI to automate testing and deployment processes.
Programming Skills : Advanced proficiency in Python programming, complemented by experience in shell scripting, enabling effective automation and integration tasks.
Deployment Tools : Familiarity with deployment tools like Helm, Kustomize, or Kapitan to manage Kubernetes configurations and streamline application releases.
Monitoring and Observability : Experience with monitoring and observability tools such as Grafana, Prometheus, or Splunk to ensure system reliability and performance.
Security Awareness : Ability to identify security risks within cloud infrastructures and implement measures to mitigate them, ensuring robust and secure systems.
Platform Development : Demonstrated experience in building secure and scalable platforms or products in cloud environments, emphasizing best practices in architecture and design.
Site Reliability Engineering (SRE) and DevOps Practices : Practical experience with modern SRE and DevOps lifecycles, tools, and frameworks, fostering a culture of automation and continuous improvement.
Adaptability and Hands-on Approach : Pragmatic and flexible, willing to engage directly in technical tasks when necessary to achieve team objectives
Preferred Qualifications
MLOps Expertise : Proficiency in MLOps frameworks and tools, such as ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC).
Domain Knowledge : Basic understanding of biology or chemistry; experience in the pharmaceutical or biotech industry is a plus.
Software Engineering Background : Strong foundation in software engineering, with a transition into technical operations roles.
Security Awareness : Ability to identify security risks and implement effective mitigation measures.
Start-up Experience : Demonstrated experience in start-up environments, showcasing adaptability and problem-solving skills.
Production Support : Experience supporting both production systems and machine learning pipelines.
Educational : Master's / Ph.D. in Computer Science, a related technical field, or equivalent practical experience.
Leadership Skills : Proven ability to lead and develop engineering teams of 3-5 members or more.
Join us as we embark on this journey to redefine the future of biology and medicine.
We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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