EXL Service
Create a free account
One signup unlocks everything for this job:
- See your personalized profile match score
- See the skills this role is missing for you
- Apply to this job and track your application
- Generate an AI cover letter for this role
Noida · On-site · 4-7 Yrs · Oct 7
Business consulting · 10000+ Employees · New York, US
In today’s digital world, data is the most powerful differentiator. Companies that leverage AI to turn data into insights and optimize workflows will be the ones to achieve market dominance. At EXL, we partner with clients using a data and AI-led approach to create services and solutions that reinvent client business models, drive better outcomes, and unlock growth at speed. As a leading data and AI company, we bring together the power of data, AI and deep industry knowledge to transform businesses, including the world’s leading corporations in industries including insurance, health, banking, media and retail, among others. Our client relationships are built on a foundation of collaboration, and we’ve been chosen as a data and AI partner by 150 Fortune 1000 / Global 2000 clients including 16 of the top 20 US, UK and AU insurers, nine of the top 15 US and UK banks, and 7 of the top 10 US health care payers. With more than 63,000 employees spanning six continents, we employ one of the largest data science teams in the industry. And we have a proven track record of more than 27 years delivering business services and running complex operations for some of the world’s best-known brands. We drive business forward with data and AI
Hiring: Engineering
What employees say
+ Good Pay & Environment which helps you to stay
− Short bench period and hard to retain talent
More reviews on the company profile.
Interview experience · Senior DevOps Engineer
Interview Rounds 1. Screening: Resume, experience, basic technical, notice period, salary. 2. Technical : GCP/GKE, Kubernetes, Terraform, networking, CI/CD, security, architecture, troubleshooting. 3. Managerial: Leader
Average difficulty · Pune · 1,211 reports
More interview insightsJob description
Overview
• Design and develop LLM-based applications using single-agent or simple multi-agent patterns for business use cases
Responsibilities
- Design and develop LLM-based applications using single-agent or simple multi-agent patterns for business use cases
- Build and maintain RAG pipelines : data ingestion chunking embeddings retrieval response generation
- Implement prompt engineering techniques (prompt templates, chaining, basic tool/function calling)
- Develop backend services/APIs for AI applications using Python frameworks (FastAPI / Flask / Streamlit)
- Integrate AI solutions with enterprise systems, databases, and APIs
- Apply basic guardrails and validation checks to improve response quality and reduce hallucination
- Work with Data Engineering teams to ensure data quality, pipeline efficiency, and proper documentation
- Collaborate with MLOps teams for deployment, monitoring, and iterative improvements
Qualifications
- 4–6 years total experience , with 1+ year hands-on experience in GenAI / LLM-based applications
- Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures
- Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
- Deep data analysis experience and handling large volume of data
- Fabric/Azure Databricks/Snowflake data engineering integration skills
- Good exposure to:
- Cloud platforms (Azure/AWS/GCP)
- SQL
- Data Engineering (ETL/ELT, pipelines, orchestration)
- Data Science / ML lifecycle (especially NLP)
- Exposure to model fine-tuning (LoRA/PEFT) or prompt optimisation techniques
- Understanding of enterprise data privacy and security considerations in GenAI
- Exposure to Azure AI / Azure OpenAI / AI Search ecosystems
- 4–6 years total experience , with 1+ year hands-on experience in GenAI / LLM-based applications
- Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures
- Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
- Deep data analysis experience and handling large volume of data
- Fabric/Azure Databricks/Snowflake data engineering integration skills
- Good exposure to:
- Cloud platforms (Azure/AWS/GCP)
Verify EXL Service for this role
Free PRACTICE for EXL Service adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify EXL Service free →Want match scores and deeper insight? Create a free candidate profile
Job application FAQ
Last updated 14 October 2026
- How do I apply for AI Data Engineer at EXL Service?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. EXL Service may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this AI Data Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is AI Data Engineer remote or on-site in Noida, Uttar Pradesh?
- This listing is marked on_site with location Noida, Uttar Pradesh. Confirm details on the job description before applying.
- What skills matter for this AI Data Engineer role at EXL Service?
- This is a mid-level AI Data Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.