Title: Google Cloud Platform DevOps Engineer
Location: Charlotte, NC (On-site)
Duration: 6 months (possibility of extension)
JD:
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 ArgoCD) 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 (Google Cloud Platform) 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/green 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 Google Cloud Platform 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.
WHAT YOU'LL BRING
Required Qualifications
Experience:
6+years of experience in DevOps, Site Reliability Engineering, or Cloud Engineering roles, or an equivalent combination of education and experience
2+ years of hands-on experience building and maintaining CI/CD pipelines (e.g., Cloud Build, Jenkins, GitLab CI/CD, GitHub Actions, or ArgoCD)
2+ years of experience with Google Cloud Platform (Google Cloud Platform) services such as GKE, Cloud Run, Cloud Functions, Cloud Build, Pub/Sub, and IAM
Experience with Infrastructure as Code tools such as Terraform or Google Cloud Deployment Manager
Experience with scripting languages such as Python, Bash, or Groovy
Education:
BA/BS in Computer Science, Information Technology, or a related field, or equivalent work experience
Technical Skills:
Working knowledge of containerization and orchestration technologies (Docker, Kubernetes/GKE)
Working knowledge of source control systems (Git, GitHub, or GitLab)
Foundational understanding of conversational AI/contact-center platforms (e.g., Google CCAI, Dialogflow CX/Conversational Agents, Kore.ai, or similar IVR/voice platforms)
Skills:
Understanding of software design patterns, principles, and the software development life cycle (SDLC)
Demonstrated verbal and written communication skills
Ability to collaborate effectively across cross-functional engineering, product, and conversational AI/NLU teams
Abilities:
Ability to read, write, speak, and understand English
Ability to deal with ambiguity, uncertainty, and incomplete information when evaluating alternatives and making recommendations
Ability to identify measures or indicators of system performance and the actions needed to improve or correct performance, relative to the goals of the system
Ability to work seamlessly within a team as well as manage individual tasks
Ability to write clear technical documentation for use by developers, testers, and operations
Preferred Qualifications
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/green 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
