Job Title

Key ResponsibilitiesAdvanced Analytics & Data ScienceDesign and develop advanced ML, NLP, deep learning, and GenAI models to solve complex business problems.Perform feature engineering, model experimentation, tuning, and validation to ensure high accuracy and robustness.Apply statistical and analytical techniques for predictive, prescriptive, and diagnostic analytics.Build domain‑aware models, particularly for insurance, financial services, and operational workflows.Generative AI & Agentic AI SolutionsDesign and implement Generative AI solutions, including LLM‑based applications, RAG pipelines, embeddings, and vector databases.Build and orchestrate agentic AI workflows, enabling multi‑agent collaboration across enterprise systems.Implement prompt engineering, evaluation frameworks, safety guardrails, and performance monitoring for GenAI systems.Contribute to EXL AI accelerators, reusable components, and platform capabilitiesData Engineering & Cloud EnablementDevelop and optimize data pipelines (batch and streaming) for large‑scale structured and unstructured data.Deploy AI models using containerization, CI/CD pipelines, and MLOps best practices.Architect and implement solutions on AWS and/or Azure, leveraging managed AI/ML and data services.Ensure security, scalability, reliability, and cost optimization of deployed solutions.Software Engineering & Production ReadinessWrite clean, modular, and testable Python code aligned with EXL engineering standards.Expose AI capabilities via APIs and microservices for enterprise consumption.Implement model monitoring, drift detection, logging, and retraining mechanisms.Support testing, performance tuning, and production issue resolution.Collaboration & Technical LeadershipWork closely with solution architects, product managers, business analysts, and domain SMEs.Mentor junior team members and contribute to capability building within EXL’s Data & AI practice.Participate in design reviews, agile ceremonies, and technical governance forums.Drive adoption of best practices, standards, and responsible AI principles.Education & ExperienceEducationBachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.Experience5–8+ years of experience in data science, machine learning, or advanced analytics.Proven experience in building and deploying production‑grade AI/ML solutions.Strong exposure to cloud‑based AI and data platforms.Hands‑on experience with NLP, GenAI, or large‑scale data solutions.Technical SkillsProgramming: Python (advanced), SQLML & AI: Supervised/unsupervised learning, NLP, deep learning, Generative AI, LLMsFrameworks: PyTorch / TensorFlow, scikit‑learn, Hugging Face (or equivalent)Data: ETL pipelines, feature engineering, vector databasesMLOps: Docker, CI/CD, experiment tracking, monitoringCloud: AWS and/or Azure AI/ML servicesPreferred / Good to HaveExperience with agentic AI frameworks or orchestration layersExposure to insurance or financial services domainContributions to AI platforms, accelerators, or reusable frameworksRelevant Cloud / AI / GenAI certificationsExperience in client‑facing or consulting rolesKey CompetenciesStrong analytical and problem‑solving skillsEngineering rigor with a production mindsetBusiness‑oriented thinking and outcome focusCollaboration and mentoring abilityContinuous learning and innovation mindsetWhy EXLWork on cutting‑edge Data, AI, and Agentic AI solutionsSolve real‑world, high‑impact business problemsBe part of a market‑leading Data & AI organizationOpportunity to shape enterprise AI platforms and future‑ready solutions