Working Hours :
Full Time
Locations :
Hyderabad
Experience :
810 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 solutionsspanning predictive analytics, optimization, NLP, and AI-driven platformsthat 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:610 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 (010)
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.
