DevOps & Cloud Infrastructure Engineer

চাকরির বিবরণ

You will own the infrastructure, CI/CD pipelines, and deployment automation that keeps WorkSprout client systems running reliably at production scale. From containerised microservices on Kubernetes to ML model serving infrastructure and IoT backend platforms, you will build the operational foundation that engineering teams rely on to ship fast without breaking things. WorkSprout is a deep-tech engineering and design partner across twelve practice areas — TinyML & Edge AI, Custom AI Development, AI Automation & Agents, Data Engineering & Collection, IoT Solutions, Hardware Prototyping, Robotics & Automation, 3D Design & Modeling, Software Development, Growth & DevOps, Branding & Creative Design, and Startup & Product Launch. We deliver systems that work in production, not just in demos. Office hours 09:00 – 18:00 BST, Monday to Friday; hybrid in Dhaka, Bangladesh. Applications are reviewed on a rolling basis. To apply, email careers@worksprout.us with the subject "DevOps & Cloud Infrastructure Engineer".

দায়িত্ব

• Design and maintain Kubernetes clusters and Docker-based deployment environments
• Build and own CI/CD pipelines using GitHub Actions, GitLab CI, or Jenkins
• Manage cloud infrastructure on AWS or GCP using Terraform or Pulumi (IaC)
• Implement monitoring, alerting, and observability stacks with Prometheus, Grafana, and ELK
• Configure secure networking, VPCs, load balancers, and TLS certificate management
• Establish and enforce security hardening, secret management, and access control policies
• Support ML platform infrastructure — GPU node pools, model serving, and training job scheduling

যোগ্যতা

• 3+ years of DevOps or platform engineering experience in production environments
• Strong Docker and Kubernetes administration experience (EKS, GKE, or self-managed)
• Infrastructure-as-Code proficiency with Terraform or Pulumi
• Experience with CI/CD pipeline design and GitOps workflows
• Knowledge of cloud networking, IAM, secrets management, and security best practices
• Nice to have: Experience with NVIDIA GPU Operator and Kubernetes-based ML workload scheduling
• Nice to have: Familiarity with service mesh tooling (Istio, Linkerd) for microservice security
• Nice to have: Knowledge of cost optimisation strategies for cloud-native and spot-instance workloads
• Nice to have: Background in SRE practices — SLOs, error budgets, and incident management

সুবিধা

• Own the infrastructure layer for diverse production AI, IoT, and software systems
• Competitive salary benchmarked to international market rates
• Flexible hybrid work arrangement with modern tooling budget
• Work on infrastructure serving clients across AI, robotics, IoT, and software products
• Direct access to cloud compute budget for experimentation and optimisation