Senior Cloud Engineer

Working Hours : Full Time Locations : Hyderabad Experience : 8–10 years apply now apply now About The Role Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning & GenAI solutions—spanning predictive analytics, optimization, NLP, and AI-driven platforms—that help leading enterprises forecast, automate, and gain a competitive edge. Behind these innovations lies robust, secure, and scalable cloud infrastructure. As part of our Cloud Engineering team, you'll help design and operate next-gen cloud systems that power cutting-edge AI solutions. Job Overview We seek a Senior Cloud Engineer to design, build, and optimize scalable, secure, and cost-efficient cloud environments. You'll collaborate with AI/ML teams to deliver production-grade systems, automate deployments, and ensure resilience of data pipelines, APIs, and AI services across AWS, Azure, and GCP. This is a hands-on role where cloud architecture meets engineering excellence. Key Responsibilities Cloud Architecture & Infrastructure Design and implement cloud-native solutions on AWS, Azure, or GCP. Build secure, highly available, and cost-optimized cloud infrastructure. Implement networking, IAM, security, and compliance best practices. Automation & DevOps Develop Infrastructure as Code (IaC) using Terraform/CloudFormation. Implement CI/CD pipelines to automate deployments for AI/ML and data platforms. Enable monitoring, logging, and alerting using cloud-native or third-party tools. Containerization & Orchestration Manage Kubernetes clusters and containerized workloads (Docker, EKS/AKS/GKE). Optimize workloads for scalability, performance, and cost efficiency. Collaboration & Support Partner with Data & AI teams to ensure cloud infra supports ML/LLM workloads (e.g., GPU provisioning, vector DB hosting). Troubleshoot complex production issues and optimize cloud operations. Mentor junior engineers on cloud best practices. Required Skills & Qualifications Education: Bachelor's/Master's in Computer Science, Cloud Computing, or related fields. Experience: 6–10 years in cloud engineering/DevOps with expertise in: Cloud Platforms: AWS, Azure, or GCP (multi-cloud experience preferred). Infrastructure as Code: Terraform, CloudFormation, Pulumi. Containers & Orchestration: Docker, Kubernetes, Helm CI/CD Tools: Jenkins, GitHub Actions, GitLab CI, or Azure DevOps Networking & Security: VPCs, IAM, firewalls, VPN, secrets management. Observability: Prometheus, Grafana, ELK, or cloud-native monitoring tools. AI/ML Enablement (preferred): GPU provisioning, supporting MLOps pipelines. Skills Matrix Candidates must submit a detailed resume and fill out the following matrix: Skill Details Skills Last Used Experience (months) Self-Rating (0–10) AWS / Azure / GCP Terraform / IaC Docker / Kubernetes CI/CD (Jenkins, GitHub Actions, etc.) Networking & Security Monitoring & Logging GPU / AI Workload Support Gen AI Deployments Instructions For Candidates Provide a detailed resume highlighting cloud projects (infrastructure automation, containerization, multi-cloud deployments, AI/ML workload support). Fill out the above skills matrix with accurate dates, duration, and self-ratings.