Data Scientist

EXL

. Develop Google CX conversational AI agents using Dialogflow CX / CX Agent Studio .

Posted 10/25/2026full-timeIndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing Google CX conversational AI agents using Dialogflow CX, with a strong focus on generative agent design, performance optimization, and API integration. Proficient in Python programming and familiar with cloud technologies to enhance agent functionality and efficiency.

Highest-signal resume keywords

Google CX DevelopmentDialogflow CX / CX Agent StudioAdvanced Python ProgrammingGoogle Cloud FunctionsLLM-Assisted Development Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingObject-Oriented ProgrammingAsynchronous PatternsGenerative Agent DesignAPI Design and RegistrationPerformance Metrics OptimizationConversational Context ManagementPagination HandlingProtocol Buffers ParsingAutomated Agent Evaluations

Tools & Technologies

Dialogflow CXGcloud CLICloud RunGoogle Cloud FunctionsSCRAPI’s Evals ModuleGemini CLIClaude Code

Industry Keywords

Conversational AIGenerative DesignVoice InteractionsAgent ArchitectureCloud Technologies

Tech Stack

Tools & technologies

CloudPythonShell Scripting

About the role

Key responsibilities & impact

Develop Google CX conversational AI agents using Dialogflow CX / CX Agent Studio
Design generative, goal-oriented agent architectures involving apps, agents, sub-agents, and sessions
Write system instructions, manage conversational memory, and optimize LLM context windows for voice interactions
Deploy agent components, webhook integrations, and backend APIs using Google Cloud Functions or Cloud Run
Configure projects and authenticate environments using gcloud CLI and application-default credentials
Design and register external APIs and tools for LLM function calling
Handle pagination, flatten API responses, and convert Protocol Buffers into usable data
Create and orchestrate automated agent evaluations, golden tests, and simulation runs
Track, analyze, and optimize agent performance metrics such as real-time latency
Use LLM-assisted IDE workflows to accelerate agent scaffolding and debugging

Requirements

What you’ll need

Bachelor's/Master's in Engineering
2–5 years of experience in engineering
At least 2–4 years of relevant experience as a Google CX Developer
Advanced Python programming using object-oriented programming, modern type hinting, and asynchronous patterns
Familiarity with uv, virtual environments (.venv), and pip
Command-line interface proficiency and general shell scripting
Knowledge of generative agent design in Dialogflow CX / CX Agent Studio
Prompt engineering and conversational context management
Understanding of Dialogflow CX fundamentals
Experience with Google Cloud Functions or Cloud Run
Proficiency with gcloud CLI and application-default credentials
Experience designing and registering external APIs for tool/function calling
Ability to handle pagination, flatten API responses, and parse Protocol Buffers
Experience creating automated agent evaluations, golden tests, and simulations using SCRAPI’s evals module
Ability to analyze and optimize agent performance metrics, including real-time latency
Experience using LLM-assisted development tools such as Gemini CLI or Claude Code