DeepRunner AI

Key Responsibilities Design and implement scalable, resilient, and cost-effective cloud architectures across AWS, Azure, and GCP. Lead Infrastructure-as-Code initiatives using Terraform, CloudFormation, and ARM templates . Architect and manage containerized environments with Docker and Kubernetes at enterprise scale. Build secure cloud networking solutions (VPCs, load balancers, firewalls, segmentation). Drive DevOps best practices , including CI/CD pipelines and automated deployment strategies. Establish and maintain cloud security frameworks aligned with SOC 2, GDPR, and industry standards. Optimize cloud spend through resource management, rightsizing, and automation tools . Design and implement data lake and big data architectures to support AI/ML workloads. Develop monitoring, logging, and observability frameworks with Prometheus, Grafana, and ELK stack. Partner with engineering teams to define technical requirements and guide architectural decisions. Lead disaster recovery and business continuity planning for mission-critical systems. Stay ahead of emerging cloud technologies and assess their business impact. Requirements Essential Qualifications Bachelor’s degree in Computer Science, Engineering, or related technical field. 8+ years of experience in cloud architecture, design, and implementation . Deep expertise in one or more cloud platforms ( AWS, Azure, GCP ). Proven track record designing and implementing scalable, resilient, and highly available solutions. Strong knowledge of cloud networking (VPC, load balancing, firewalls). Hands-on experience with IaC tools (Terraform, CloudFormation, ARM). Proficiency in containerization (Docker), orchestration (Kubernetes) , and serverless technologies. Solid background in DevOps practices and cloud cost optimization . Knowledge of cloud security & compliance standards (SOC 2, GDPR). Experience with data lakes and big data technologies in the cloud. Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK). Excellent communication and collaboration skills. Preferred Qualifications Master’s degree in Computer Science, Engineering, or related field. Multiple cloud certifications (e.g., AWS Solutions Architect Pro, Azure Architect Expert, GCP Professional Architect ). Experience with AI/ML infrastructure and MLOps pipelines . Advanced knowledge of microservices architecture and service mesh (Istio, Envoy, Helm). Experience with multi-cloud and hybrid cloud architectures and enterprise migrations. Knowledge of advanced security practices (Zero-Trust, PCI-DSS, HIPAA). Experience leading technical teams, mentoring engineers, and managing cloud budgets > $1M . Exposure to chaos engineering, edge computing, and CDN architectures . Previous experience in a startup or high-growth technology company . Work Location: This role can also be based in Athens or the San Francisco Bay Area