Senior Data Scientist – Generative AI & LLM Engineering

Practice - AIA - Artificial Intelligence and Analytics

About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.

By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery model

s. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.

Job Summary

We are seeking a Senior Data Scientist with strong expertise in Exploratory Data Analysis (EDA), Machine Learning, Generative AI, and Large Language Models (LLMs). This role will focus on designing, tuning, evaluating, optimizing, and deploying enterprise-scale AI/ML solutions while contributing to the broader AI architecture roadmap. The ideal candidate will combine strong statistical and machine learning foundations with hands-on experience in RAG, LLM tuning, AI agents, model evaluation, and production AI platforms.

In this role, you will:

• Perform advanced Exploratory Data Analysis (EDA) and statistical analysis to identify patterns, relationships, anomalies, and actionable business insights.
• Design, develop, evaluate, and deploy machine learning models for predictive analytics, classification, regression, forecasting, and other enterprise use cases.
• Build Generative AI and LLM-based solutions, including RAG applications, AI agents, enterprise search, and knowledge-driven AI systems.
• Fine-tune, profile, benchmark, and optimize LLMs for model quality, latency, accuracy, scalability, and cost efficiency.
• Design model evaluation frameworks covering performance, relevance, hallucination, safety, robustness, and business effectiveness.
• Contribute to end-to-end AI/ML architecture across cloud and on-premises environments, including model serving, data pipelines, and integration patterns.
• Develop and operationalize MLOps/LLMOps pipelines for experimentation, versioning, deployment, monitoring, and continuous model improvement.
• Evaluate AI/ML frameworks, foundation models, vector databases, and emerging technologies based on business and technical requirements.
• Collaborate with data engineers, AI engineers, architects, product teams, and business stakeholders to translate requirements into scalable AI solutions.
• Ensure AI solutions follow enterprise security, data governance, responsible AI, and production-readiness standards.

What you need to have to be considered

• 6+ years of experience in Data Science, Machine Learning, AI Engineering, or Advanced Analytics roles.
• Expert knowledge of Exploratory Data Analysis, statistical methods, feature engineering, machine learning algorithms, and model evaluation techniques.
• 3+ years of strong hands-on Machine Learning experience developing and deploying production-grade models.
• Hands-on experience with Generative AI and LLMs, including prompt engineering, RAG, embeddings, vector databases, model tuning, evaluation, and performance optimization.
• Strong proficiency in Python and ML/AI frameworks such as Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, or equivalent technologies.
• Experience with LLM fine-tuning approaches, model benchmarking, inference optimization, and responsible AI practices.
• Familiarity with AI agents, multi-agent systems, MLOps/LLMOps, model monitoring, and enterprise AI platform architecture.
• Experience with major cloud AI/ML platforms such as Azure, AWS, or GCP and production deployment practices.
• Strong analytical, problem-solving, communication, and stakeholder collaboration skills with the ability to translate technical results into business outcomes.

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Applications will be accepted until 30 Oct 2026.

Salary and Other Compensation:

The annual salary for this position is between $[133,000 - 156,500] depending on experience and other…