
3 Days Left) Senior Cloud Engineer
3 weeks ago
Location: Hyderabad
Experience: 8–10 years
Job Type: Full-time
About Us
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.
Please submit skills matrix in tabular format having the following columns:
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:
1. Provide a detailed resume highlighting cloud projects (infrastructure automation, containerization, multi-cloud deployments, AI/ML workload support).
2. Fill out the above skills matrix with accurate dates, duration, and self-ratings.
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