Senior DevOps Engineer, Arine

• The ideal candidate will have extensive experience with Amazon Web Services (AWS), a strong background in DevOps practices, and a passion for leveraging AI and machine learning to drive automation and operational excellence
• The ideal candidate will have a strong AWS background, specifically around scaled AWS Lambda-based, data-centric infrastructures, along with hands-on experience deploying and managing Kubernetes clusters and containerized workloads at scale
• Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience)
• 7+ years of experience in DevOps or Cloud Engineering roles
• 5+ years of hands-on experience with AWS services, including API Gateway, Lambda, EC2, S3, ECS, BatchJobs, Lambda, RDS, DynamoDB, OpenSearch, VPC, CloudFormation, and IAM
• Proven experience with automation tools and Infrastructure as Code (IaC), including Terraform, AWS CDK, AWS SAM
• 5+ years of expertise in CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI/CD, or similar)
• 5+ years of production experience with Kubernetes, including EKS, cluster administration, Helm, and GitOps practices
• Proficiency with version control systems (e.g., Git) and containerization tools (e.g., Docker, ECR, ECS)
• Strong scripting/programming skills in Python, Bash, or JavaScript
• Experience with Kubernetes ecosystem tools, including Helm, Kustomize, ArgoCD/Flux, and service meshes (Istio, Linkerd)
• Knowledge of security principles, monitoring tools, and logging frameworks (e.g., CloudWatch, ELK stack, Prometheus, Grafana)
• Knowledge of networking fundamentals, including DNS, VPN, and load balancing in cloud environments
• Excellent problem-solving skills and the ability to work under pressure
• Strong communication and collaboration skills to work effectively with cross-functional teams
• An established private work area that ensures information privacy
• A stable high-speed internet connection for telephonic and/or remote work
• Ability to pass a background check
• Must live in and be eligible to work in the United States

Desirable

• Arine is seeking a highly motivated and technically strong Senior DevOps Engineer to help build, automate, and scale our cloud infrastructure and delivery pipelines
• This role will focus on AWS, CI/CD, and Infrastructure as Code, while also leveraging AI-driven tooling to improve reliability, security, and delivery speed. You will work closely with Engineering, QA, and Security teams to ensure fast, safe, and scalable software delivery
• We are seeking a skilled and motivated Senior DevOps Engineer to join our dynamic team at Arine Inc
• As a Senior DevOps Engineer, you will be responsible for designing, implementing, and maintaining cloud infrastructure as code deployments, ensuring the scalability, security, and reliability of our cloud-based applications
• You will collaborate closely with development, operations, and security teams to automate workflows and improve overall system performance
• This position will support, maintain, and develop software using a variety of different tools, including AWS stacks and expertise in CI/CD tools
• This candidate will also be expected to lead the evolution of our CI/CD pipeline, branching and release strategies, and support our drive towards automated testing
• You will play a key role in integrating AI-powered tools and intelligent automation into our DevOps workflows to enhance efficiency, predictability, and system resilience
• Cloud Infrastructure Management:
• Design, deploy, and manage scalable, secure, and reliable AWS cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation
• Monitor and manage EC2 instances and other services like RDS and ECS, ensuring optimal performance, scalability, and availability. Manage auto-scaling to handle varying workloads
• Design, deploy, and operate Kubernetes clusters (EKS or self-managed) for containerized workloads, implementing best practices for cluster security, networking, and resource management
• Optimize cloud resources for cost-effectiveness and performance, including monitoring AWS service costs and implementing cost-saving strategies
• Spin up new infrastructure from existing configurations within a week to meet urgent project requirements
• Deploy, automate, and maintain releases using release/change management processes
• Build, release, and manage production systems, and troubleshoot system issues
• Administer, deploy, automate, and manage Jenkins
• Collaborate with onshore, offshore, and nearshore dev and QA teams
• AI-Powered Automation and Intelligent Operations:
• Leverage AI/ML tools and platforms (e.g., GitHub Copilot, Claude) to accelerate infrastructure development, code review, and documentation
• Implement AIOps practices using AI-driven monitoring and anomaly detection to proactively identify issues before they impact production
• Build and maintain AI-assisted incident response workflows, including automated root cause analysis and intelligent alerting
• Evaluate and integrate emerging AI tools into the DevOps toolchain to improve developer productivity and operational efficiency
• Develop intelligent automation pipelines that leverage ML models for predictive scaling, capacity planning, and resource optimization
• Automation and Scripting:
• Create and manage automation scripts for routine tasks using Python, Bash, or similar scripting languages
• Implement automated monitoring and alerting solutions to proactively detect and resolve issues
• Create automation scripts using Jenkins
• Build self-healing infrastructure using AI-driven automation to detect and remediate common issues without manual intervention
• Kubernetes and Container Orchestration:
• Deploy, manage, and scale Kubernetes clusters on AWS EKS, ensuring high availability and optimal resource utilization
• Implement Kubernetes best practices, including namespaces, RBAC, network policies, resource quotas, and pod security standards
• Design and manage Helm charts, Kustomize configurations, and GitOps workflows (ArgoCD, Flux) for Kubernetes deployments
• Troubleshoot complex Kubernetes issues, including networking, storage, and scheduling problems
• Implement service mesh solutions (Istio, Linkerd) for advanced traffic management, observability, and security
• Security and Compliance:
• Ensure the security and compliance of AWS environments by implementing best practices, including IAM policies, security groups, VPC configurations, and encryption
• Conduct regular security assessments and audits in collaboration with the security team, identifying and addressing vulnerabilities
• Ensure security and adherence to the release/change management process for production releases
• Implement Kubernetes security best practices, including pod security policies, secrets management, and container image scanning
• Collaboration and Support:
• Work closely with development teams to understand application requirements and provide guidance on best practices for cloud architecture and DevOps processes
• Provide on-call support for production environments, including troubleshooting and resolving issues as they arise
• Collaborate with cross-functional teams to improve overall system reliability and performance
• Adaptable and resilient in a fast-moving startup setting, with the ability to handle ambiguity and evolving priorities
• Monitoring and Optimization:
• Set up and maintain monitoring tools such as CloudWatch, Prometheus, or Datadog to ensure the health and performance of applications
• Monitor EC2 instances, Kubernetes clusters, and other AWS services for performance, availability, and cost-efficiency, taking proactive steps to optimize them
• Ensure high availability of systems, implementing redundancy and failover mechanisms to minimize downtime
• Analyze and optimize system performance, including load balancing, caching, and database tuning
• Implement observability best practices across Kubernetes workloads using distributed tracing, metrics, and centralized logging
• Documentation and Training:
• Document infrastructure, processes, and procedures for knowledge sharing and compliance purposes
• Provide training and mentorship to junior team members on best practices in AWS, Kubernetes, and DevOps
• Champion AI-assisted tooling adoption and train teams on the effective use of AI coding assistants and automation tools