AI/ML Engineer

Cognizant is seeking a Senior AI/ML Engineer to design, develop, and deliver production-ready AI solutions for complex enterprise business challenges. The role focuses on machine learning, NLP, generative and agentic AI, scalable data pipelines, MLOps, and collaboration with cross-functional teams to deliver governed solutions.

Responsibilities:

• Design, develop, and deploy production-grade AI and Machine Learning solutions
• Build and maintain advanced Generative AI and Agentic AI applications utilizing multi-agent orchestration frameworks
• Develop Retrieval-Augmented Generation (RAG) solutions and Natural Language-to-SQL (Text-to-SQL) applications
• Create and optimize LLM evaluation, monitoring, observability, and governance frameworks
• Design scalable NLP solutions, including text classification, semantic search, topic modeling, sentiment analysis, and embedding-based applications
• Develop and deploy machine learning models using statistical and deep learning techniques
• Build high-performance data pipelines and AI workflows using Python, PySpark, SQL, and cloud-native technologies
• Implement MLOps best practices including CI/CD, model validation, monitoring, drift detection, and automated quality controls
• Collaborate with stakeholders to understand business requirements and deliver scalable AI solutions aligned with organizational objectives
• Ensure AI systems adhere to enterprise governance, security, compliance, and responsible AI standards
• Contribute to AI platform architecture, solution modernization initiatives, and continuous improvement efforts

Requirements:

• Bachelor's degree in computer science, Data Science, Engineering, Mathematics, or a related field
• 8+ years of experience in Machine Learning, Artificial Intelligence, Data Science, or related disciplines
• Strong hands-on experience developing and deploying enterprise AI/ML solutions in production environments
• Proven experience with Generative AI technologies, including RAG, agent-based systems, prompt engineering, and LLM evaluation
• Expertise in Python and AI/ML libraries such as PyTorch, TensorFlow, Scikit-Learn, and Hugging Face
• Experience with LangGraph and/or LangChain for AI application development
• Strong knowledge of NLP techniques including classification, semantic similarity, embeddings, clustering, and topic modeling
• Experience designing and implementing scalable data pipelines using SQL and PySpark
• Experience deploying solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform
• Knowledge of containerization and orchestration technologies including Docker and Kubernetes
• Experience implementing MLOps practices, including model deployment, monitoring, validation, CI/CD, and observability
• Strong communication skills with the ability to translate technical concepts into business value
• this role is not able to offer visa transfer or sponsorship now or in the future