Junior DevOps Engineer

Join our team as a Junior DevOps Engineer, where you will design, build, and scale secure infrastructure supporting AI workloads across cloud and edge environments. This high-impact individual contributor role will involve driving infrastructure architecture, platform reliability, and security best practices across the organization. You will work closely with engineering teams to implement scalable, automated infrastructure solutions that enable our AI platform to operate efficiently across diverse deployment scenarios.

• Design and implement secure, scalable infrastructure across multi-cloud (AWS, Azure, GCP), hybrid, and edge environments.
• Build and maintain Infrastructure as Code (Terraform, Pulumi, Ansible) using GitOps workflows and automated validation.
• Deploy and operate Kubernetes clusters optimized for AI/ML workloads, including GPU scheduling and container security best practices.

• This role requires strong technical depth, production experience, and the ability to translate complex requirements into resilient infrastructure systems
• Foundational understanding of cloud security, identity, permissions, and access management
• Understanding of monitoring, logging, and observability concepts
• Hands-on experience or familiarity with Infrastructure as Code tools such as Terraform, Pulumi, or Ansible
• Familiarity with CI/CD concepts and tools such as GitHub Actions, GitLab CI, Jenkins, or ArgoCD
• Strong communication skills and ability to collaborate with developers and other technical teams
• Familiarity with Docker and containerized application environments; exposure to Kubernetes is a plus
• Familiarity with Git and modern software development workflows
• Strong troubleshooting and problem-solving skills with an eagerness to learn
• Basic programming or scripting experience with Python, Go, Bash, or similar languages for automation
• 1–3 years of experience in DevOps, Infrastructure Engineering, Software Engineering, or a related technical role
• Experience working with or learning cloud platforms such as AWS, Azure, or GCP, including basic compute, networking, and managed services
• Exposure to Kubernetes or other container orchestration technologies
• Exposure to Infrastructure as Code through professional experience, personal projects, internships, or coursework
• Interest in supporting AI/ML or MLOps infrastructure and workflows
• Familiarity with multi-cloud or hybrid cloud environments
• Familiarity with service mesh technologies such as Istio or Linkerd
• Exposure to edge computing or distributed systems
• Basic understanding of cloud cost optimization and resource efficiency
• Relevant entry-level or associate certifications such as AWS Certified Cloud Practitioner, AWS Solutions Architect – Associate, Azure Fundamentals, or Terraform Associate