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Soothsayer Analytics logo

Senior Cloud Engineer

10 years

0 Lacs

hyderabad telangana india

Posted:1 day ago| Platform: Linkedin logo

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Skills Required

analytics ai data design learning optimization forecast automate engineering power cutting ml aws azure gcp architecture networking iam security compliance automation devops code terraform monitoring logging containerization orchestration kubernetes docker scalability collaboration support provisioning jenkins github gitlab vpn enablement duration

Work Mode

On-site

Job Type

Full Time

Job Description

Working Hours :

Full Time

Locations :

Hyderabad

Experience :

8–10 years

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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 / GCPTerraform / IaCDocker / KubernetesCI/CD (Jenkins, GitHub Actions, etc.)Networking & SecurityMonitoring & LoggingGPU / AI Workload SupportGen 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.

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