Description

Key Responsibilities
• Agent Architecture & Implementation: Design, build, train, and test conversational flows, intents, custom route groups, and LLM-powered tools within Google Cloud Platform using GECX / Dialogflow CX.
• Full-Stack & Backend Integration: Develop robust RESTful APIs, webhooks, and microservices in .NET, Python, or Node.js to integrate conversational agents with ServiceNow and Azure enterprise systems.
• DevOps & Pipeline Automation: Build, maintain, and enhance automated CI/CD pipelines in Azure DevOps for environment provisioning, validation, and continuous deployment of agent configurations and fulfillment services.
• Automated Quality Engineering: Implement automated test suites covering unit logic, webhook APIs, dialog flow regressions, and end-to-end conversational journeys.
• Data Querying & Performance Tuning: Write and optimize complex SQL queries for conversational analytics, reporting, and backend data operations.
• Agile Execution: Actively participate in SAFe Agile ceremonies, including Program Increment (PI) planning, sprint execution, backlog refinement, and cross-team dependency mapping.

Required Skills & Qualifications
1. Deep Conversational AI Expertise (GECX / Dialogflow CX): Proven track record of designing, building, and deploying enterprise-scale virtual agents using Google Cloud Platform conversational frameworks, specifically GECX / Dialogflow CX, including state handlers, route groups, webhook fulfillment, condition rules, and generative agent capabilities.
2. Core Polyglot Development (.NET, Python, TypeScript, JavaScript): Extensive hands-on experience building backend services, API fulfillment webhooks, and asynchronous workflows using .NET (C#) alongside Python, TypeScript, and JavaScript.
3. Automated Testing & Quality Engineering: Strong hands-on experience implementing automated testing strategies for conversational systems and APIs—including unit testing, mock services, integration testing, and regression test suites for dialog flows using modern test frameworks (e.g., NUnit/xUnit, PyTest, Jest, or Postman/Newman).
4. Automated CI/CD Implementation in Azure DevOps: Demonstrated mastery in designing and configuring production-ready CI/CD pipelines in Azure DevOps (YAML pipelines, release gates, automated linting, test execution, and deployment artifacts).
5. Enterprise Multi-Cloud Integration (Azure & ServiceNow): In-depth experience integrating distributed cloud services across multi-cloud environments, specifically connecting conversational agents with ServiceNow APIs (Incident, Change, Service Catalog, Flow Designer) and Azure services.
6. Advanced SQL & Enterprise Data Operations: Strong proficiency in writing complex SQL queries, relational database modeling, and data manipulation to support dynamic agent lookups, reporting, and transactional verification.
7. SAFe Agile Methodology Experience: Solid experience operating within a Scaled Agile Framework (SAFe) enterprise environment, actively engaging in Program Increment (PI) planning, sprint iterations, user story sizing, and coordinating cross-functional ART (Agile Release Train) dependencies.
8. Modern Development Workflow & Tooling (VS Code / Antigravity): Fluency with professional developer toolchains, Git-based version control, and proficiency coding, debugging, and running local emulations inside modern IDE environments like VS Code or Antigravity.
9. AI Agent Architecture & Fallback Orchestration: Demonstrated capability to architect fault-tolerant conversational agent interactions, context and session variable management, prompt engineering, intent classification, and seamless human escalation / fallback workflows.
10. Enterprise Security & Cloud Fundamentals: Practical knowledge of securing multi-cloud integrations, including OAuth2, API key management, role-based access control (RBAC), and secrets handling across GCP, Azure, and ServiceNow.

Preferred / Nice-to-Have Qualifications
• Familiarity with Contact Center AI (CCAI) architectures and telephony/voice gateway integrations.
• Experience with Site Reliability Engineering (SRE) principles, telemetry/observability, and AIOps event correlation.
• Experience with containerization (Docker, Kubernetes) and serverless deployment models (Cloud Run, Google Cloud Functions, Azure Functions).

Tooling & Environment
• Conversational AI & Cloud: Google Cloud Platform (GECX / Dialogflow CX, Vertex AI), Microsoft Azure
• Languages & Runtimes: .NET (C#), Python 3.x, Node.js / TypeScript / JavaScript, SQL
• DevOps & Testing: Azure DevOps (Pipelines, Repos), Git, Automated API/Unit Testing Frameworks
• Enterprise Platforms: ServiceNow (REST APIs, Flow Designer)
• Agile Framework: SAFe (Scaled Agile Framework), Jira / Azure Boards
• Development Environments: Visual Studio Code (VS Code), Antigravity

Key Skills

Education

Bachelor's degree