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Data Scientist

EXL • Bachelor's Degree • Python • SQL • 3 days ago
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Salary
≈ $19k – $38k per year (Estimated)
Location
In office (Noida)
Seniority
Senior · 5+ years exp

Confirmed on the employer's own hiring board on Oct 2, 2026. First seen by Alion on Sep 29, 2026. EXL scores B on the Alion truth index.

Overview
Company
Impact
Profile match

EXL

EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.
exlservice.com • HQ: New York, United States • 5000+ employees • Est. 1999
Tech stack of EXL

Key Responsibilities

Leadership & Strategy

  • Lead architectural design and implementation of multi-agent AI systems
  • Drive technical strategy for GenAI initiatives and recommend best practices
  • Mentor and provide technical guidance to junior and mid-level engineers
  • Collaborate with stakeholders to define requirements and deliver solutions
  • Own end-to-end delivery of complex, production-scale AI systems

Technical Execution

  • Build and maintain high-performance REST/WebSocket APIs using FastAPI (Pydantic v2)
  • Implement and optimize agentic AI systems using frameworks like LangGraph, Deep Agents, AutoGen, and LangChain
  • Architect real-time, event-driven microservices using messaging queues like Apache Kafka
  • Design clean, testable, maintainable services using SOLID principles, Python async, and type hints
  • Integrate and optimize SQL, NoSQL, and vector databases (Postgres, MongoDB, ChromaDB, Pinecone)
  • Run LangGraph/Deep Agents workflows in production with checkpointing, persistence, and human-in-the-loop controls, backed by LLM observability and evaluation tooling (e.g., LangSmith, Langfuse)
  • Apply LLM safety guardrails (prompt-injection mitigation, PII handling, content moderation) in line with Banking, Insurance, and Healthcare compliance requirements
  • Stay current with emerging trends in GenAI, deep learning, and AI orchestration framework

Skills and Competencies

  • Proven ability to architect and deliver end-to-end GenAI solutions and multi-agent systems
  • Strong software engineering discipline: testing (unit, integration, performance), code review, documentation
  • Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders
  • Strategic thinking and problem-solving with a focus on scalability and maintainability

  • Leadership capability: mentoring, technical guidance, and cross-functional collaboration

Key Responsibilities

Leadership & Strategy

  • Lead architectural design and implementation of multi-agent AI systems
  • Drive technical strategy for GenAI initiatives and recommend best practices
  • Mentor and provide technical guidance to junior and mid-level engineers
  • Collaborate with stakeholders to define requirements and deliver solutions
  • Own end-to-end delivery of complex, production-scale AI systems

Technical Execution

  • Build and maintain high-performance REST/WebSocket APIs using FastAPI (Pydantic v2)
  • Implement and optimize agentic AI systems using frameworks like LangGraph, Deep Agents, AutoGen, and LangChain
  • Architect real-time, event-driven microservices using messaging queues like Apache Kafka
  • Design clean, testable, maintainable services using SOLID principles, Python async, and type hints
  • Integrate and optimize SQL, NoSQL, and vector databases (Postgres, MongoDB, ChromaDB, Pinecone)
  • Run LangGraph/Deep Agents workflows in production with checkpointing, persistence, and human-in-the-loop controls, backed by LLM observability and evaluation tooling (e.g., LangSmith, Langfuse)
  • Apply LLM safety guardrails (prompt-injection mitigation, PII handling, content moderation) in line with Banking, Insurance, and Healthcare compliance requirements
  • Stay current with emerging trends in GenAI, deep learning, and AI orchestration framework

Skills and Competencies

  • Proven ability to architect and deliver end-to-end GenAI solutions and multi-agent systems
  • Strong software engineering discipline: testing (unit, integration, performance), code review, documentation
  • Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders
  • Strategic thinking and problem-solving with a focus on scalability and maintainability

  • Leadership capability: mentoring, technical guidance, and cross-functional collaboration

Minimum Qualifications

  • Bachelor's degree in Computer Science, Data Science, or related field
  • 5+ years of total professional experience, including:
  • 3+ years of hands-on Software Engineering experience in Python, FastAPI and relevant tech stack
  • 2+ years working specifically with GenAI and LLMs (GPT, Claude, LLaMA, etc.)
  • Track record of shipping production ML/AI products, with strong prompt-engineering skills, systems-level thinking, and the ability to diagnose and resolve production failures
  • Strong software engineering background with expertise in OOP and SOLID principles
  • Proficiency in Python 3.11+ (async/await, type hints, modern Python patterns, strict type checking)
  • Experience with agentic frameworks (LangChain, LangGraph, AutoGen, or similar)
  • Proven track record building production REST/WebSocket APIs and microservices
  • Experience with message streaming platforms (Kafka, Pulsar, or similar)
  • Strong knowledge of databases: SQL, NoSQL, and vector databases
  • Working knowledge of RAG pipelines (embeddings, chunking, retrieval) and LLM observability/evaluation tools (LangSmith, Langfuse, or similar)
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