Junior AI Agent Developer

About the Role

We're looking for an AI Agent Developer to help build, test, and support enterprise conversational AI agents and the web experiences around them. You'll work alongside senior engineers on Google Cloud Platform (GECX / Dialogflow CX), connect agents to Azure and ServiceNow, build front-end interfaces that users interact with, and help maintain the pipelines and tests that keep releases reliable.

Key Responsibilities

• Agent and backend
• Agent development: Build and test conversational flows, intents, route groups, and LLM-powered tools in GECX / Dialogflow CX, and contribute to agents built with Google's Agent Development Kit (ADK).
• Backend integration: Develop and maintain REST APIs, webhooks, and small services in Python (.NET or Node.js) that connect agents to ServiceNow and Azure systems.
• Data queries: Write SQL queries for agent lookups, reporting, and conversational analytics.
• Front end
• Web UI development: Create responsive, accessible interfaces using HTML, CSS, and TypeScript / JavaScript with a modern framework (e.g., React or Angular).
• API connection: Connect front-end components to backend services and agent APIs, including loading states, error handling, and session handling in the browser.
• Dashboards and tools: Contribute to simple internal pages for agent analytics, test results, or admin tasks.
• Delivery
• CI/CD support: Help maintain Azure DevOps pipelines used to validate and deploy agent configurations, fulfillment services, and front-end builds. Make updates to existing YAML pipelines with review.
• Automated testing: Write and run unit tests, webhook API tests, dialog flow regression tests, and front-end component tests. Help expand coverage over time.
• Troubleshooting: Investigate bugs and failed test runs, document findings, and escalate when needed.
• Agile participation: Take part in sprint planning, standups, backlog refinement, and Program Increment (PI) planning within a SAFe environment.
• Documentation: Keep flow designs, API behavior, UI component notes, and runbooks current.

Requirements & Tech Stack

• Tooling & Environment
• Conversational AI & Cloud: Google Cloud Platform (GECX / Dialogflow CX), Microsoft Azure
• Back end: Python 3.x (primary), .NET (C#), Node.js, SQL
• Front end: HTML, CSS, TypeScript / JavaScript, a modern framework (e.g., Angular or React)
• DevOps & Testing: Azure DevOps (Pipelines, Repos), Git, API, unit, and UI testing frameworks
• Enterprise Platforms: ServiceNow (REST APIs, Flow Designer)
• Agile: SAFe, Jira / Azure Boards
• IDEs: Visual Studio Code, Antigravity

Qualifications

• Bachelor's degree in Computer Science, IT, or a related field, or equivalent practical experience.
• Working proficiency in Python (required), .NET and HTML, CSS, and JavaScript or TypeScript.
• Understanding of REST APIs, JSON, MCP and how webhooks work, including calling APIs from a browser app.
• SQL skills.
• Experience with Git and a modern IDE such as VS Code.
• Exposure to unit testing with a framework like PyTest, Jest, or xUnit.
• Clear written and verbal communication, and willingness to ask questions and take feedback.

Preferred Qualifications (not explicitly required for the role)

• Hands-on exposure to Dialogflow CX, chatbots, or any LLM-based application (coursework or personal projects are fine).
• Exposure to Google's Agent Development Kit (ADK) or similar agent frameworks.
• Basic knowledge of prompt engineering and intent classification.
• Familiarity with front-end testing tools such as Jest, Selenium, or Playwright / Cypress.
• Familiarity with Azure DevOps pipelines or another CI/CD tool.
• Exposure to .NET (C#), ServiceNow (REST APIs, Flow Designer), or both.
• Basic understanding of OAuth2, API keys, secrets handling, and browser security basics (CORS, avoiding XSS).
• Awareness of Agile or SAFe practices.
• Familiarity with containers and infrastructure as code (Docker, Kubernetes, or Terraform).
• Familiarity with serverless platforms (Cloud Run, Azure Functions) or Contact Center AI (CCAI).
• Interest in SRE, observability, and AIOps.