Join our AI & Innovation group as a DevOps Engineer and play a critical role in the infrastructure and deployment of cutting-edge AI-driven solutions. As the owner of our cloud-based production environment for our flagship product, Infinity AI Copilot, you will ensure seamless operations, oversee infrastructure, CI/CD pipelines, and deployment strategies, ensuring robust, scalable, and reliable operations across Azure and AWS.

Major Responsibilities

• Infrastructure Management: Own and maintain the cloud-based infrastructure supporting Infinity AI Copilot, including managing EKS in AWS and related Azure environments.
• CI/CD Pipelines: Develop, optimize, and manage CI/CD pipelines to ensure seamless and efficient deployments of AI and software solutions.
• Database Administration: Manage and optimize a variety of database solutions, including relational databases, vector databases, and graph databases
• Monitoring and Troubleshooting: Implement and maintain monitoring tools to ensure performance, reliability, and scalability of deployments.
• Automation: Automate provisioning, deployment, and scaling processes using tools like Terraform and Kubernetes.
• Collaboration: Partner with ML engineers, software developers, and data scientists to integrate machine learning workflows into production environments.
• Security and Compliance: Enforce best practices in cloud security, ensuring compliance with industry standards and regulations.
• Scaling: Monitor system resources and optimize configurations to enable efficient scaling to meet dynamic demands.

Desired Background

• Experience: 4-5 years in a DevOps or related role, with experience managing large-scale cloud environments.
• Cloud Expertise: Strong experience with AWS, with expertise in managing EKS and related cloud-native technologies.
• Kubernetes & Containerization: Proficiency with Kubernetes, Docker, and Helm for deploying and managing containerized environments.
• Database Skills: Hands-on experience managing diverse databases, including relational, vector, and graph database solutions.
• Infrastructure as Code (IaC): Proficiency with Terraform, CloudFormation, or similar tools for managing cloud resources.
• CI/CD Expertise: Strong understanding of CI/CD pipelines and tools such as Jenkins, GitHub Actions, or equivalent.
• Monitoring Tools: Experience with monitoring and logging solutions such as Prometheus, Grafana, ELK Stack, or similar.
• Scripting: Proficient in scripting languages like Python, Bash, or Groovy for task automation.
• Security: Knowledge of implementing cloud security standards and maintaining compliance.

Advantages

• Familiarity with AI/ML deployment challenges and workflows.
• Experience with multi-cloud or hybrid cloud strategies.
• Background in managing high-performance, low-latency systems.