Time since we first saw it
Day 37
Similar jobs usually come down between day 4 and day 77.
At EXL Service, jobs usually come down by about day 21.
From 51 similar postings that came down, and 281 of EXL Service’s. Coming down is not always a hire.
Data Scientist
Reads like an AI Engineer role: building products on existing AI models.
Noida, Uttar Pradesh, India
Live, first seen by us 37 days ago- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingBuild generative agent components in Dialogflow CX / CX Agent Studio
Design and register external APIs as tools the LLM can call
Deploy webhooks and backend APIs on Cloud Functions or Cloud Run
Track and optimize agent performance metrics such as real-time latency
From the employer’s posting
Generative Agent Design: Shifting from legacy intent-based state machines to generative, goal-oriented architectures
Designing and registering external APIs ("Tools") that the LLM can invoke
Deploying agent components, webhook integrations, or backend APIs using Google Cloud Functions or Cloud Run
Extracting, analyzing, and optimizing agent performance metrics (like real-time latency)
Education & alternatives
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
Tools in this posting
- Python
- Shell
- GCP
Source — Tool mentions in context
Key Skills: Python Python Programming (Advanced):. You must be proficient in Python, utilizing object-oriented programming, modern type hinting, and asynchronous patterns.
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.
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
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)
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.
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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 7, 202637 days ago
- Recorded sightings
- 181
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EXL Service is hiring
211 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
- 5% of open jobs were reposted
Your next step
Check the employer’s posting for the current role and application details.
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Has EXL Service posted this job before?
Yes. We’ve followed 6 other Data Scientist jobs there since October 2026. All 6 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About EXL Service
- People
- About 65,000 in 2025, up 9% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as EXLS.
Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Noida, Uttar Pradesh, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
AI answers unavailable
We couldn’t identify enough role detail in this saved description to support an AI answer. Read the full posting