Senior Cloud Engineer

1 day ago

Hyderabad, Telangana, India Soothsayer Analytics Full time
Job Title: Senior Cloud Engineer Location: Experience: 8–10 years

Job Type: Full-time

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.

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.

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

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.

Manage Kubernetes clusters and containerized workloads (Docker, EKS/AKS/GKE).

Optimize workloads for scalability, performance, and cost efficiency.

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.

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).

Docker, Kubernetes, Helm.

CI/CD Tools: Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

Networking & Security: VPCs, IAM, firewalls, VPN, secrets management.

Prometheus, Grafana, ELK, or cloud-native monitoring tools.

AI/ML Enablement (preferred): GPU provisioning, supporting MLOps pipelines.

Skill, Details, Skills Last Used, Experience (months), Self-Rating (0–10)

AWS / Azure / GCP

Docker / Kubernetes

Networking & Security

Monitoring & Logging

GPU / AI Workload Support

Gen AI Deployments

Provide a detailed resume highlighting cloud projects (infrastructure automation, containerization, multi-cloud deployments, AI/ML workload support).

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