GCP Agentic AI DevOps Engineer

Design, build, and maintain CI/CD pipelines (e.g., Cloud Build, Jenkins, GitLab CI/CD, GitHub Actions, or Argo CD that deploy and version Google CCAI/Conversational Agents (CXAS) agent configurations, playbooks, flows, and supporting webhook services. Configure and maintain monitoring, logging, and alerting (e.g., Cloud Monitoring, Cloud Logging, Datadog) for both the CI/CD pipeline and the production agentic AI platform, including deployment health, latency, and error-rate signals***.

Job title: GCP Agentic AI DevOps Engineer
Work Location: Charlotte, NC 28273
Duration of the project: 6 Months

Detailed Job Description:
Actively and consistently support all efforts to simplify and enhance the customer experience.
Design, build, and maintain CI/CD pipelines (e.g., Cloud Build, Jenkins, GitLab CI/CD, GitHub Actions, or Argo CD that deploy and version Google CCAI/Conversational Agents (CXAS) agent configurations, playbooks, flows, and supporting webhook services.
Automate provisioning and configuration of Google Cloud Platform (GCP) infrastructure including GKE, Cloud Run, Cloud Functions, Pub/Sub, Cloud Build, and IAM using Infrastructure as Code (e.g., Terraform).
Work with developers, testers, QA, and deployment teams to plan and execute releases across development, test, staging, and production CXAS environments.
Write and maintain automated deployment scripts and progressive rollout strategies (blue/. or canary) to minimize risk and downtime for a customer-facing production system.
Configure and maintain monitoring, logging, and alerting (e.g., Cloud Monitoring, Cloud Logging, Datadog) for both the CI/CD pipeline and the production agentic AI platform, including deployment health, latency, and error-rate signals***
Support the integration pipeline between the Kore.ai IVR platform and Google CXAS, including webhook, API, and telephony-transfer configuration changes.
Partner with security and compliance teams to remediate vulnerabilities, manage GCP IAM roles/policies, and enforce least-privilege access across projects handling customer data.
Serve as a point of contact for production support, troubleshooting CI/CD pipeline and deployment-related issues for the agentic AI platform.
Maintain clear documentation for pipeline architecture, deployment runbooks, and operational procedures.
Participate in project-related stand-up meetings, sprint planning, and on-call rotation.

The top 3 responsibilities would expect the Subcon to shoulder and execute:
Support the integration pipeline between the Kore.ai IVR platform and Google CXAS, including webhook, API, and telephony-transfer configuration changes
Foundational understanding of conversational AI/contact-center platforms (e.g., Google CCAI, Dialogflow CX/Conversational Agents, Kore.ai, or similar IVR/voice platforms).
Google Cloud certification (e.g., Professional Cloud DevOps Engineer or Associate Cloud Engineer).
Hands-on experience with Google Customer Engagement AI (CCAI) / Conversational Agents (Dialogflow CX/CXAS), including agent versioning, environments, and deployment.

Must have skills:
1. 8 years of experience in DevOps, Site Reliability Engineering, or Cloud Engineering roles, or an equivalent combination of education and experience.
2. Hands-on experience building and maintaining CI/CD pipelines (e.g., Cloud Build, Jenkins, GitLab CI/CD, GitHub Actions, or ArgoCD).
3. 2 years of experience with Google Cloud Platform (GCP) services such as GKE, Cloud Run, Cloud Functions, Cloud Build, Pub/Sub, and IAM.
4. Experience with Infrastructure as Code tools such as Terraform or Google Cloud Deployment Manager.
5. Experience with scripting languages such as Python, Bash, or Groovy.
6. Working knowledge of containerization and orchestration technologies (Docker, Kubernetes/GKE).
7. Working knowledge of source control systems (Git, GitHub, or GitLab).
8. Foundational understanding of conversational AI/contact-center platforms (e.g., Google CCAI, Dialogflow CX/Conversational Agents, Kore.ai, or similar IVR/voice platforms).
9. Understanding of software design patterns, principles, and the software development life cycle (SDLC).
10. Demonstrated verbal and written communication skills.
11. Ability to collaborate effectively across cross-functional engineering, product, and conversational AI/NLU teams.

Good to Have Skills
Google Cloud certification (e.g., Professional Cloud DevOps Engineer or Associate Cloud Engineer).
Hands-on experience with Google Customer Engagement AI (CCAI) / Conversational Agents (Dialogflow CX/CXAS), including agent versioning, environments, and deployment.
Experience integrating cloud CI/CD pipelines with third-party IVR/contact-center platforms (e.g., Kore.ai) via APIs or webhooks.
Familiarity with monitoring/observability tools such as Cloud Monitoring, Datadog, or Grafana.
Experience with blue/. or canary deployment strategies for customer-facing production systems.
Knowledge of security and compliance practices for cloud-hosted customer support systems that process personally identifiable information (PII).
Relevant Experience on Mandatory Skills: 8-10 years