Owns hands-on deployment, integration, and stabilization of AI agents in Intel's environment. Acts as the full-stack data / ADK engineer with master-level grasp of complex ADK builds and Finance/HR workflows, bridging engineering and operations to accelerate go-live and adoption.
Key Responsibilities
Deploy agents to Gemini Enterprise Agent Engine, Cloud Run, or GKE with IAM, VPC-SC, and Model Armor.
Build and maintain CI/CD pipelines, environment configuration, and secrets management.
Integrate complex ADK agents with enterprise data sources and Finance/HR workflows.
Troubleshoot integration, performance, and reliability issues; enable observability and tracing.
Drive early adoption, feedback loops, and rapid iteration with Intel users; lead hypercare/stabilization.
Mandatory (Must-Have) Skills
Master-level ADK and full-stack data engineering skills.
Complex Finance/HR workflow knowledge and enterprise integration.
Strong Python; hands-on GKE, Cloud Run, Agent Engine, Terraform, Cloud Build/Deploy.
Google Cloud IAM, VPC-SC, and security controls.
Preferred (Good-to-Have) Skills
Data extraction/normalization from Databricks, ServiceNow, Snowflake, OneDrive, Adobe.
Vertex AI, observability tooling, SRE practices.
Customer-facing deployment experience.
Experience & Certifications
7+ years DevOps/SRE/cloud engineering with 1+ year GenAI deployments.
Google Cloud Professional certification preferred.
Must be able to work onsite in the USA.
or continue with email
Key Responsibilities
Deploy agents to Gemini Enterprise Agent Engine, Cloud Run, or GKE with IAM, VPC-SC, and Model Armor.
Build and maintain CI/CD pipelines, environment configuration, and secrets management.
Integrate complex ADK agents with enterprise data sources and Finance/HR workflows.
Troubleshoot integration, performance, and reliability issues; enable observability and tracing.
Drive early adoption, feedback loops, and rapid iteration with Intel users; lead hypercare/stabilization.
Mandatory (Must-Have) Skills
Master-level ADK and full-stack data engineering skills.
Complex Finance/HR workflow knowledge and enterprise integration.
Strong Python; hands-on GKE, Cloud Run, Agent Engine, Terraform, Cloud Build/Deploy.
Google Cloud IAM, VPC-SC, and security controls.
Preferred (Good-to-Have) Skills
Data extraction/normalization from Databricks, ServiceNow, Snowflake, OneDrive, Adobe.
Vertex AI, observability tooling, SRE practices.
Customer-facing deployment experience.
Experience & Certifications
7+ years DevOps/SRE/cloud engineering with 1+ year GenAI deployments.
Google Cloud Professional certification preferred.
Must be able to work onsite in the USA.
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