Description
Desired Skills and Experience:
- 7 - 10 years of experience with architecting, designing and implementing end-to-end cloud infrastructure solutions across leading Cloud platforms with a special focus on Azure and Google Cloud Platform
- Hands‑on experience in Python development with the ability to design and build proof-of-concept (POC) Generative AI and Agentic AI use cases, leveraging services such as Google Cloud Vertex AI, Azure AI Foundry, and Microsoft Copilot Studio.
- Familiarity with Large Language Models (LLM) application development frameworks, Retrieval‑Augmented Generation (RAG) architectures is valuable to have.
- Must have skills –
- Cloud Infrastructure Architecture – Demonstrated expertise in architecting secure, scalable, and resilient hybrid and cloud-native infrastructure solutions on Azure and GCP, with deep knowledge of cloud services, networking, IAM, cost optimization, multi-cloud strategies, and hands-on experience with the pillars of the well-architected framework.
- Design and Development of AI Solutions on Cloud – Basic understanding and hands-on experience designing cloud infrastructure solutions to support AI/Generative AI/Agentic AI proof-of-concept use cases / solutions using either of the below platforms:
- Google Cloud Vertex AI (Prompt Design, Agent Builder, Vector Search, LLM orchestration, Tooling)
- Azure AI Foundry / Azure OpenAI (Prompt Flow, Agent orchestration, Model deployments)
- Microsoft Copilot Studio (Plugins, custom connectors, enterprise data grounding, agent behavior design)
- Strong hands-on Python development experience will be preferred.
- Infrastructure-as-Code (IaC) and Configuration Management – Hands-on expertise in Infrastructure as Code (IaC) and configuration management leveraging tools such as Terraform, Ansible, python scripting etc. with a strong track record of automating cloud infrastructure provisioning, ensuring consistency and compliance across multi-cloud and hybrid environments.
- DevOps
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🏢 BSR
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