Data Engineer
EXL Talent Acquisition Team
Senior AI Data Engineer
About this role
Key Responsibilities
- Design and develop LLM-powered applications using agentic patterns (single/multi-agent) for business use cases
- Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis)
- Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs)
- Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications
- Integrate LLM solutions with enterprise systems, data platforms, and workflows
- Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage
- Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling
- Contribute to reusable components, documentation, and engineering best practices
Experience & Core Requirements (Must-Have)
Overall Experience
- 6–9 years total experience
- 1–3+ years in hands-on GenAI / LLM application development (production use cases)
LLM / GenAI & Agentic Engineering
- Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures
- Deep understanding of:
- LLM limitations, evaluation, and optimisation strategies
Core Engineering
- 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
- Containers, CI/CD, monitoring
Data / AI Foundations (Mandatory)
Prior experience in one or more:
- Data Engineering (ETL/ELT, pipelines, orchestration)
- Data Science / ML lifecycle (especially NLP)
- Analytics engineering / data products
Good-to-Have / Preferred
- Experience with fine-tuning techniques (LoRA, PEFT) or prompt tuning strategies
- Experience with enterprise GenAI security & privacy practices (data masking, access control, compliance)
- Familiarity with Azure AI ecosystem (Azure OpenAI, Azure AI Search, Fabric, etc.)
- Exposure to agentic coding tools (e.g., Claude Code or similar environments)
Key Responsibilities
- Design and develop LLM-powered applications using agentic patterns (single/multi-agent) for business use cases
- Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis)
- Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs)
- Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications
- Integrate LLM solutions with enterprise systems, data platforms, and workflows
- Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage
- Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling
- Contribute to reusable components, documentation, and engineering best practices
Experience & Core Requirements (Must-Have)
Overall Experience
- 6–9 years total experience
- 1–3+ years in hands-on GenAI / LLM application development (production use cases)
LLM / GenAI & Agentic Engineering
- Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures
- Deep understanding of:
- LLM limitations, evaluation, and optimisation strategies
Core Engineering
- 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
- Containers, CI/CD, monitoring
Data / AI Foundations (Mandatory)
Prior experience in one or more:
- Data Engineering (ETL/ELT, pipelines, orchestration)
- Data Science / ML lifecycle (especially NLP)
- Analytics engineering / data products
Good-to-Have / Preferred
- Experience with fine-tuning techniques (LoRA, PEFT) or prompt tuning strategies
- Experience with enterprise GenAI security & privacy practices (data masking, access control, compliance)
- Familiarity with Azure AI ecosystem (Azure OpenAI, Azure AI Search, Fabric, etc.)
- Exposure to agentic coding tools (e.g., Claude Code or similar environments)
Key Responsibilities
- Design and develop LLM-powered applications using agentic patterns (single/multi-agent) for business use cases
- Build and optimise end-to-end RAG pipelines (ingestion, embeddings, retrieval, orchestration, response synthesis)
- Implement prompt engineering and orchestration techniques (prompt chaining, tool/function calling, structured outputs)
- Develop production-grade APIs and services (FastAPI/Flask/Streamlit) for GenAI applications
- Integrate LLM solutions with enterprise systems, data platforms, and workflows
- Apply guardrails and evaluation frameworks to improve response quality, reduce hallucinations, and ensure responsible AI usage
- Collaborate with Data Engineering and MLOps teams for data pipelines, deployment, monitoring, and scaling
- Contribute to reusable components, documentation, and engineering best practices
Experience & Core Requirements (Must-Have)
Overall Experience
- 6–9 years total experience
- 1–3+ years in hands-on GenAI / LLM application development (production use cases)
LLM / GenAI & Agentic Engineering
- Strong hands-on experience with:
- LLMs (Claude, OpenAI, etc.)
- RAG pipelines and retrieval optimisation
- GPT + Agentic AI implementation experience
- Experience with:
- LangChain, LangGraph, or similar frameworks
- Agent orchestration and tool-calling architectures
- Deep understanding of:
- LLM limitations, evaluation, and optimisation strategies
Core Engineering
- 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
- Containers, CI/CD, monitoring
Data / AI Foundations (Mandatory)
Prior experience in one or more:
- Data Engineering (ETL/ELT, pipelines, orchestration)
- Data Science / ML lifecycle (especially NLP)
- Analytics engineering / data products
Good-to-Have / Preferred
- Experience with fine-tuning techniques (LoRA, PEFT) or prompt tuning strategies
- Experience with enterprise GenAI security & privacy practices (data masking, access control, compliance)
- Familiarity with Azure AI ecosystem (Azure OpenAI, Azure AI Search, Fabric, etc.)
- Exposure to agentic coding tools (e.g., Claude Code or similar environments)
Frequently Asked Questions
Is the salary disclosed for the Senior AI Data Engineer position at EXL Talent Acquisition Team?
The salary for this Senior AI Data Engineer role at EXL Talent Acquisition Team is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Senior AI Data Engineer position at EXL Talent Acquisition Team located?
This Senior AI Data Engineer role at EXL Talent Acquisition Team is based in Noida, Uttar Pradesh, India. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
How do I apply for the Senior AI Data Engineer position at EXL Talent Acquisition Team?
Click the "Apply Now" button on this page. You will be redirected to EXL Talent Acquisition Team's official application portal hosted on oraclecloud where you can submit your application directly.
When was the Senior AI Data Engineer job at EXL Talent Acquisition Team posted?
This Senior AI Data Engineer position at EXL Talent Acquisition Team was posted on Jul 8, 2026. Apply as soon as possible — early applications are often reviewed first.
Senior AI Data Engineer
EXL Talent Acquisition Team
You'll be redirected to EXL Talent Acquisition Team's official application page on oraclecloud.