Responsibilities
As a DevOps Engineer, Cloud Toolchain, your main responsibilities will be to:
• automated processes fimplementation, security, monitoring, alerting operations using Terraform, Ansible, YAML, Python environment-specific scripting languages
• Develop maintain a platform of integrated systems tools to support Agile DevOps practices across a diverse set of workflows used by multiple development teams across the company
• Help run our toolchain infrastructure using Ansible, Terraform Kubernetes
• Design build re-usable templates to accomplish specific workflow use cases
• Perform incremental testing actions on code, processes, deployments to identify ways to streamline execution minimize errors
• Continually document all actions work to define repeatable actions that can be automated
• Design, implement, support system monitoring infrastructure
• Continually improve our monitoring, metrics automated response capabilities
• Collaborate with team members to tackle complex technological infrastructure, security, development problems
• Provide direct responsive support favailability incidents other urgent analytic, development operational needs
• Debug production issues across services, at all component levels respond to after-hours escalations
• Use our toolchain service offering fyour day-to-day activities work with the toolchain team to continually improve it
Education, Experience, Certifications
• Undergraduate degree in Computer Science equivalent area of technical study
• 3-5 years of hands-on production programming experience with agile software development in a variety of languages, such as Python, .NET/C#, Go, Java, JavaScript/Node.JS
• AWS Solution Architect certification within the last 12 months, with a strong preference fprofessional grade certification
• Additional DevOps Certifications by a majcloud infrastructure provider and/CNCF related technology provider within the last 24 months, AWS preferred
Technical Qualifications:
• Minimum 5 years of infrastructure automation experience, at least 3 years of that managing production environments fmultiple foundational services available in AWS, Azure and/GCP, deep understanding of the AWS Well Architected Framework.
• Design, develop, maintain robust backend systems using MLFlow, Kubernetes, Databricks Docker.
• Hands-on experience integrating AI/ML solutions cloud-native environments (e.g., AWS SageMaker), with a focus on scalability, monitoring, reliability.
• Ability to evaluate implement AI-driven solutions to optimize infrastructure provisioning, incident response, system performance.
• Operationalize Deploy machine learning models to solve complex problems enhance platform functionality leveraging MLFlow frameworks.
• Solid understanding of machine learning concepts, algorithms, frameworks such as TensorFlow, PyTorch, scikit-learn
• A minimum of 3 years hands-on staging production experience in each of the following areas
• Infrastructure configuration management including Terraform Ansible
• Administering deploying development CI/CD tools such as GitLab, Jenkins, Azure DevOps.
• Containers containerchestration services, especially Docker & Kubernetes
• Systems administration scripting methods such as Python, Bash PowerShell.
• Supporting Windows Linux operating system environments
• Network architecture, including load-balancing, DNS, BGP, IPSec VPNs
Other Qualifications:
• Demonstrated systems perspective when analyzing problems, thinking about overall operation, failure modes how to address these problems proactively
• A strong sense fthe importance of documentation, the importance of not having to learn things twice
• Ability to work in an agile product team environment balance a diverse set of stakeholder requests
• Excellental written communication skills with an ability to break down complex technical systems to help business partners understthe value
• Strong technical collaboration communication skills as well as the ability to drive cultural change adoption of best practices through community participation
• Ability to collaborate with other teams across the company, defining technology roadmaps, sharing experiences lessons learned fcontinual improvement
• Excellent problem-solving troubleshooting skills
• Process-oriented with great documentation skills
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