Senior AI Engineer

EXL

Senior AI Engineer defining the technical vision and leading development for Google Contact Center AI initiatives. Focus on CCAI Agent Assist and Dialogflow CX with robust solutions.

Posted 7/8/2026full-time🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing solutions using CCAI Agent Assist and Dialogflow CX, with a strong foundation in Python programming and cloud technologies. Capable of leading development initiatives and optimizing conversational AI systems for enhanced user interactions.

Highest-signal resume keywords

Python ProgrammingDialogflow CXGoogle Cloud FunctionsConversational AI OptimizationObject-Oriented Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonObject-Oriented ProgrammingAsynchronous PatternsShell ScriptingGenerative ArchitecturesAPI DesignAutomated TestingConversational Memory ManagementLLM Context OptimizationWebhook Integration

Tools & Technologies

CCAI Agent AssistDialogflow CXGcloudCloud RunVirtual EnvironmentsCLI ToolsPython Package Managers

Certifications & Qualifications

Bachelor Degree in Relevant Field

Industry Keywords

Conversational AIVoice InteractionsAgent Performance MetricsProject Configuration

Tech Stack

Tools & technologies

CloudPythonShell Scripting

About the role

Key responsibilities & impact

Defining the technical vision, designing robust solutions with a primary focus on CCAI Agent Assist and Dialogflow CX
Leading the end-to-end development of Google Contact Center AI (CCAI) initiatives

Requirements

What you’ll need

Bachelor Degree in relevant field with 6- 8 years of relevant experience
Proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns
Familiarity with modern Python package managers like uv, virtual environments (.venv), and pip
Ability to navigate CLI tools, as well as general shell scripting
Understanding of generative, goal-oriented architectures
Writing robust system instructions, managing conversational memory, and optimizing LLM context windows for voice interactions
Understanding the underlying mechanics of Dialogflow CX
Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run
Utilizing gcloud for project configuration and authenticating environments via application-default credentials
Designing and registering external APIs that the LLM can invoke
Using utility functions to handle pagination and flatten API responses
Creating and orchestrating automated tests and evaluating agent performance metrics

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development