Job Summary

- Senior cloud engineers / architects for the first three to four months to support design & deployment decisions for the platform as it goes live across the enterprise.
- Lead the architecture, design, and deployment of cloud-native AI Operations platform components across enterprise environments, ensuring scalability, resilience, and security.
- Define and implement cloud infrastructure standards, networking, identity management, and governance controls for production-grade AI workloads.
- Support platform deployment decisions, including compute, storage, containerization, orchestration, and multi-region high-availability configurations.
- Collaborate with AI/ML, DevOps, Security, and Operations teams to establish CI/CD pipelines, Infrastructure-as-Code (IaC), and automated deployment frameworks.
- Conduct technical reviews, architecture assessments, and performance optimization activities to ensure operational readiness before enterprise-wide rollout.
- Establish observability, monitoring, logging, and incident response mechanisms for proactive management of AI services and supporting cloud infrastructure.
- Provide hands-on guidance and technical oversight during go-live phases, troubleshooting complex cloud infrastructure issues and mitigating deployment risks.
- Define operational runbooks, architecture blueprints, security guardrails, and knowledge transfer plans to enable a sustainable transition to the AI Operations support team.

Key Responsibilities





- Senior cloud engineers / architects for the first three to four months to support design & deployment decisions for the platform as it goes live across the enterprise.
- Lead the architecture, design, and deployment of cloud-native AI Operations platform components across enterprise environments, ensuring scalability, resilience, and security.
- Define and implement cloud infrastructure standards, networking, identity management, and governance controls for production-grade AI workloads.
- Support platform deployment decisions, including compute, storage, containerization, orchestration, and multi-region high-availability configurations.
- Collaborate with AI/ML, DevOps, Security, and Operations teams to establish CI/CD pipelines, Infrastructure-as-Code (IaC), and automated deployment frameworks.
- Conduct technical reviews, architecture assessments, and performance optimization activities to ensure operational readiness before enterprise-wide rollout.
- Establish observability, monitoring, logging, and incident response mechanisms for proactive management of AI services and supporting cloud infrastructure.
- Provide hands-on guidance and technical oversight during go-live phases, troubleshooting complex cloud infrastructure issues and mitigating deployment risks.
- Define operational runbooks, architecture blueprints, security guardrails, and knowledge transfer plans to enable a sustainable transition to the AI Operations support team.

Skill Requirements

Must Have Skill

Apigee APIM,RESTful API,Qdrant,GCP AI & ML (CCAI/Vertex AI/GenAI),Model Context Protocol (MCP)

Positive to Have Skill

Other Requirements

📌 Technical Support Specialist (India)
🏢 HCLTech
📍 India