Job description: GECX Developer
Key Skills:
Python
Python Programming (Advanced):. You must be proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns.
Environment & Dependency Management: Familiarity with modern Python package managers like uv, virtual environments (.venv), and pip.
Command Line Interface (CLI) Proficiency: Ability to navigate CLI tools, as well as general shell scripting
Conversational AI / Agent Architecture (Dialogflow CX)
Generative Agent Design: Shifting from legacy intent-based state machines to generative, goal-oriented architectures (understanding Apps, Agents, Sub-agents, and Sessions within CX Agent Studio).
Prompt Engineering & Context Management: Writing robust system instructions, managing conversational memory, and optimizing LLM context windows for voice interactions.
Dialogflow CX Fundamentals: Understanding the underlying mechanics of Dialogflow CX.
Google Cloud Platform (GCP)
Cloud Compute & Serverless: Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run.
Gcloud CLI Mastery: Utilizing gcloud for project configuration and authenticating environments via application-default credentials.
API Integration & Tool Building
Tool Calling / Function Calling: Designing and registering external APIs ("Tools") that the LLM can invoke to retrieve data, execute backend tasks, or interact with external services.
Data Handling & Payload Parsing: Using utility functions to handle pagination, flatten API responses, and convert complex Protocol Buffers (Protos) into usable data.
Testing, Evaluation & CI/CD
Automated Agent Evaluation (Evals): Creating and orchestrating "Golden tests" and automated simulation runs using SCRAPI’s evals module.
Performance Metrics Tracking: Extracting, analyzing, and optimizing agent performance metrics (like real-time latency), which is highly critical for voice voice interactions.
Agentic IDE workflows: Using LLM-assisted development tools (like Gemini CLI or Claude Code) as integrated into the SCRAPI workflow to speed up agent scaffolding and debugging.
Job description: GECX Developer
Key Skills:
Python
Python Programming (Advanced):. You must be proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns.
Environment & Dependency Management: Familiarity with modern Python package managers like uv, virtual environments (.venv), and pip.
Command Line Interface (CLI) Proficiency: Ability to navigate CLI tools, as well as general shell scripting
Conversational AI / Agent Architecture (Dialogflow CX)
Generative Agent Design: Shifting from legacy intent-based state machines to generative, goal-oriented architectures (understanding Apps, Agents, Sub-agents, and Sessions within CX Agent Studio).
Prompt Engineering & Context Management: Writing robust system instructions, managing conversational memory, and optimizing LLM context windows for voice interactions.
Dialogflow CX Fundamentals: Understanding the underlying mechanics of Dialogflow CX.
Google Cloud Platform (GCP)
Cloud Compute & Serverless: Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run.
Gcloud CLI Mastery: Utilizing gcloud for project configuration and authenticating environments via application-default credentials.
API Integration & Tool Building
Tool Calling / Function Calling: Designing and registering external APIs ("Tools") that the LLM can invoke to retrieve data, execute backend tasks, or interact with external services.
Data Handling & Payload Parsing: Using utility functions to handle pagination, flatten API responses, and convert complex Protocol Buffers (Protos) into usable data.
Testing, Evaluation & CI/CD
Automated Agent Evaluation (Evals): Creating and orchestrating "Golden tests" and automated simulation runs using SCRAPI’s evals module.
Performance Metrics Tracking: Extracting, analyzing, and optimizing agent performance metrics (like real-time latency), which is highly critical for voice voice interactions.
Agentic IDE workflows: Using LLM-assisted development tools (like Gemini CLI or Claude Code) as integrated into the SCRAPI workflow to speed up agent scaffolding and debugging.
Job description: GECX Developer
Key Skills:
Python
Python Programming (Advanced):. You must be proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns.
Environment & Dependency Management: Familiarity with modern Python package managers like uv, virtual environments (.venv), and pip.
Command Line Interface (CLI) Proficiency: Ability to navigate CLI tools, as well as general shell scripting
Conversational AI / Agent Architecture (Dialogflow CX)
Generative Agent Design: Shifting from legacy intent-based state machines to generative, goal-oriented architectures (understanding Apps, Agents, Sub-agents, and Sessions within CX Agent Studio).
Prompt Engineering & Context Management: Writing robust system instructions, managing conversational memory, and optimizing LLM context windows for voice interactions.
Dialogflow CX Fundamentals: Understanding the underlying mechanics of Dialogflow CX.
Google Cloud Platform (GCP)
Cloud Compute & Serverless: Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run.
Gcloud CLI Mastery: Utilizing gcloud for project configuration and authenticating environments via application-default credentials.
API Integration & Tool Building
Tool Calling / Function Calling: Designing and registering external APIs ("Tools") that the LLM can invoke to retrieve data, execute backend tasks, or interact with external services.
Data Handling & Payload Parsing: Using utility functions to handle pagination, flatten API responses, and convert complex Protocol Buffers (Protos) into usable data.
Testing, Evaluation & CI/CD
Automated Agent Evaluation (Evals): Creating and orchestrating "Golden tests" and automated simulation runs using SCRAPI’s evals module.
Performance Metrics Tracking: Extracting, analyzing, and optimizing agent performance metrics (like real-time latency), which is highly critical for voice voice interactions.
Agentic IDE workflows: Using LLM-assisted development tools (like Gemini CLI or Claude Code) as integrated into the SCRAPI workflow to speed up agent scaffolding and debugging.
Bachelor's/Master's in Engineering 5-8 years
Skills Required
- Bachelor's or Master's degree in Engineering
- 5–8 years of experience
- Advanced Python programming, including object-oriented programming, type hinting, and asynchronous patterns
- Familiarity with uv, virtual environments, and pip
- Command-line interface and shell scripting proficiency
- Dialogflow CX and generative conversational agent architecture experience
- Prompt engineering and conversational context management experience
- Google Cloud Platform, Cloud Functions, Cloud Run, and gcloud CLI experience
- API integration, tool calling, function calling, and Protocol Buffer payload handling
- Automated agent evaluation, golden tests, simulation runs, and performance metrics tracking
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
