EXL

Analyzes business data and runs outsourced operations

Data Scientist

AI Application Engineering +1Confirmed live in the last 24 hours

Full-timeGurugram, Haryana, IndiaNo salary listedIn-person

About the Job

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, AI/ML, or a related field.
At least 3 years of total professional experience in AI/ML, Data Science, or related fields.
At least 3 years of hands-on Python experience with strong software engineering practices.
At least 3 years of AI/ML engineering experience, including at least 2 years of hands-on Generative AI or Agentic AI experience.
Hands-on experience with deep learning frameworks such as PyTorch and TensorFlow.
Expertise in large language models, prompt engineering, and fine-tuning.
A proven track record of deploying at least 3 GenAI or Agentic AI projects into production.
A strong background in Data Science or Data Engineering, including data pipelines, ETL, and data modeling.
Practical knowledge of SQL, NoSQL, vector databases, and graph databases.
Familiarity with agentic AI frameworks such as LangGraph, AutoGen, and LangChain or similar frameworks.
Experience with multi-agent systems and orchestration of intelligent workflows.
Knowledge of MLOps practices, including CI/CD, model monitoring, and retraining pipelines.
Contributions to open-source AI/ML projects or published research in generative AI.
Bachelor's or Master's degree in Engineering; 2–5 years of experience.

Responsibilities

Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks.
Architect and optimize scalable REST and WebSocket APIs for production deployment.
Develop, fine-tune, and integrate large language models into enterprise applications.
Deploy and maintain at least 3 GenAI or Agentic AI projects in production, ensuring reliability, scalability, and performance.
Integrate SQL, NoSQL, and vector databases such as Postgres, MongoDB, and ChromaDB.
Implement graph databases such as Neo4j for knowledge graph-based use cases.
Provide technical leadership and mentorship to engineering teams.
Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains.
Ensure robustness, security, and compliance of deployed AI systems.
Stay current with trends in GenAI, deep learning, and orchestration frameworks.
Document and present technical solutions to technical and non-technical audiences.

Desired Qualifications

Strong problem-solving skills and ability to thrive in fast-paced R&D environments.

Lead the design and implementation of agentic AI workflows using LangGraph, AutoGen, LangChain, or similar frameworks.
Architect and optimize scalable APIs (REST/WebSocket) for production deployment.
Develop, fine-tune, and integrate large language models into enterprise applications.
Deploy and maintain at least 3 GenAI/Agentic AI projects in production, ensuring reliability, scalability, and performance.
Integrate SQL, No-SQL, and vector databases such as Postgres, MongoDB, and ChromaDB.
Implement graph databases (Neo4j) for knowledge graph-based use cases.
Provide technical leadership and mentorship to engineering teams.
Collaborate with cross-functional stakeholders to identify and deliver GenAI solutions across multiple business domains.
Ensure robustness, security, and compliance of deployed AI systems.
Stay current with trends in GenAI, deep learning, and orchestration frameworks.
Document and present technical solutions to both technical and non-technical audiences.
Familiarity with LangGraph, AutoGen, LangChain, or similar agentic AI frameworks.
Experience with multi-agent systems and orchestration of intelligent workflows.
Knowledge of MLOps practices (CI/CD, model monitoring, retraining pipelines).
Strong problem-solving skills and ability to thrive in fast-paced R&D environments.
Contributions to open-source AI/ML projects or published research in generative AI.

Bachelor's/Master's in Engineering 2-5 years

Bachelor’s or Master’s degree in Computer Science, Data Science, Data Engineering, AI/ML, or related field.
3+ years of total professional experience in AI/ML, Data Science, or related fields.
3+ years of hands-on experience in Python with strong software engineering practices.
At least 3 years of experience in AI/ML engineering, including 2+ years of hands-on experience in Generative AI /Agentic AI.
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow).
Expertise in large language models (LLMs), prompt engineering, and fine-tuning.
Proven track record of deploying at least 3 GenAI/Agentic AI projects into production.
Strong background in Data Science or Data Engineering, including data pipelines, ETL, and data modeling.
Practical knowledge of SQL, No-SQL, vector databases, and graph databases.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size: 10,001+
Company stage: IPO
Headquarters: New York City, New York
Founded: 1999

Recently Posted Jobs

Explore more opportunities at EXL

See more jobs