Lead AWS DevOps Engineer
Research InnovationsFull Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Candidates should possess a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience, with at least 5 years of professional experience as a DevOps Engineer or in a similar role. Extensive experience with Amazon Web Services (AWS), including AWS certification, is required, along with proficiency in at least one programming language like Python, Java, or Go. Strong proficiency in infrastructure-as-code (IaC) tools, preferably CloudFormation, and good understanding and practical experience using and deploying AI (ML, LLMs) are essential. Expertise in automating cloud-native technologies, deploying applications, and provisioning infrastructure, along with experience with cloud-native CI/CD workflows and tools such as Github Actions or AWS CodeDeploy, is necessary. Familiarity with microservices architecture, containerization, and orchestration tools like Docker and Kubernetes, a solid understanding of Linux basics, networking fundamentals, and security best practices, and excellent communication skills are also required.
The DevOps Engineer will collaborate with product and engineering teams to drive and enhance the entire lifecycle of products, from design and development to deployment and operation. They will work closely with clients to deploy and troubleshoot products in clients' AWS environments, ensuring smooth integration and optimal performance. Responsibilities include developing CloudFormation templates, Terraform modules, Python scripts, deployment frameworks, monitors, and self-healing tools to automate processes and improve efficiency. The engineer will assist the software engineering team in building accurate monitoring and metrics systems for applications before they go into production. They will manage internal AWS environments and network, ensuring stability, security, and scalability while controlling costs. Additionally, the role involves participating in meetings with potential clients, working alongside solution architects to address their questions and concerns regarding product integration into client networks and AWS accounts, and maintaining up-to-date documentation on deployments, processes, and standard operating procedures.
Cloud platform for scientific data management
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.