AI Architect

EXL

. Design and develop generative, goal-oriented conversational AI agents .

Posted 10/22/2026full-timeNoida • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing generative conversational AI agents, with a strong focus on Python programming, API integration, and performance optimization in cloud environments. Proficient in managing conversational memory and utilizing advanced tools for automated evaluations and debugging.

Highest-signal resume keywords

Advanced Python ProgrammingGoogle Cloud FunctionsConversational Memory ManagementAPI IntegrationAutomated Agent Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Object-Oriented ProgrammingAsynchronous PatternsPrompt EngineeringData HandlingPaginationProtocol Buffers ParsingLLM Context-Window OptimizationShell ScriptingAPI Response FlatteningGcloud CLI Proficiency

Tools & Technologies

Dialogflow CXSCRAPI's Evals ModuleGemini CLIClaude CodeCloud Run

Certifications & Qualifications

Bachelor's Degree

Industry Keywords

Generative AIConversational AIGoal-Oriented AgentsAgent ArchitecturesVoice Interactions

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformPythonShell Scripting

About the role

Key responsibilities & impact

Design and develop generative, goal-oriented conversational AI agents
Build and integrate external API tools for LLM function calling
Deploy agent components, webhook integrations, and backend APIs on Google Cloud Functions or Cloud Run
Configure GCP projects and authenticate environments using gcloud CLI and application-default credentials
Manage conversational memory, system instructions, and LLM context windows for voice interactions
Handle pagination, flatten API responses, and parse Protocol Buffers data
Create and orchestrate automated agent evaluations, Golden tests, and simulation runs using SCRAPI's evals module
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 Degree
Advanced Python programming using object-oriented programming, modern type hinting, and asynchronous patterns
Familiarity with uv, virtual environments (.venv), and pip
CLI proficiency and general shell scripting
Understanding of generative, goal-oriented agent architectures, including Apps, Agents, Sub-agents, and Sessions within CX Agent Studio
Prompt engineering, conversational memory management, and LLM context-window optimization for voice interactions
Understanding of Dialogflow CX fundamentals
Experience deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run
Proficiency with gcloud CLI, project configuration, and application-default credentials
Ability to design and register external APIs/tools for LLM tool or function calling
Data handling, pagination, API response flattening, and Protocol Buffers parsing
Automated agent evaluation using Golden tests, simulation runs, and SCRAPI's evals module
Ability to analyze and optimize agent performance metrics, including real-time latency
Experience with LLM-assisted development tools such as Gemini CLI or Claude Code