HCLTech—Technical Support Specialist

Job description

Description: 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 Other Requirements