| Bengaluru, KarnatakaPune, Maharashtra
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
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