DevOps Engineer

• 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 (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/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 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.

DevOps, Customer Experience, Cloud Computing, Jenkins, GitHub, Continuous Integration, Continuous Deployment/Delivery, GCP (Good Clinical Practices), Quality Assurance, Production Systems, * 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)
• Experience with Google Cloud Platform (GCP) 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

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 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, * 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)