Manager-Data & ML Engg

We are seeking an experienced ModelOps Lead to drive enterprise-scale AI, Generative AI, and ModelOps initiatives across Machine Learning and LLM platforms. The ideal candidate will have 7+ years strong hands-on expertise in AI Engineering, GenAI, RAG, Agentic AI, MLOps, LLMOps, AI Governance, and Observability, along with working knowledge of Data Engineering, Power Platform, Data Science, and DevOps practices. The role involves leading the end-to-end AI lifecycle, from solution design and development through deployment, monitoring, governance, and continuous optimization while ensuring scalability, reliability, compliance, and business value realization.AI Engineering & ModelOps Leadership

Responsibilities

• Lead the design, development, deployment, and operationalization of AI, Generative AI, RAG and Agentic AI solutions.
• Define and execute enterprise ModelOps, MLOps, and LLMOps strategies across AI platforms.
• Establish governance, monitoring, observability, and support frameworks for AI applications and models.
• Drive AI platform modernization, innovation, and continuous improvement initiatives.

• Deploy, monitor, evaluate, and optimize ML and GenAI models.
• Support development of AI powered business solutions leveraging Power BI, Power Apps, and Power Automate.
• Define and track model performance, explainability, fairness, governance, and business impact metrics.

• Build and manage CI/CD/CT pipelines for ML and LLM deployments.
• Implement model registries, experiment tracking, versioning, monitoring, and observability frameworks.
• Establish controls for model drift, data drift, hallucinations, prompt injection, toxicity, latency, and cost optimization.
• Implement Responsible AI, Model Risk Management, compliance, privacy, explainability, and governance controls.

• Act as a trusted advisor for client AI transformation programs and GenAI adoption initiatives.
• Lead architecture reviews, governance discussions, workshops, executive presentations, and solutioning activities.
• Support AI strategy engagements, estimations, and RFP responses.
• Manage delivery, resource planning, stakeholder communication, and capability-building initiatives.

Required Skills

• Strong expertise in Generative AI, LLMs, RAG Architectures, Agentic AI, Prompt Engineering, AI Agents, Azure OpenAI, Azure AI Foundry, LangChain, LangGraph, and Semantic Kernel.
• Hands-on experience with MLOps, LLMOps, MLflow, Kubeflow, PromptFlow, Model Registries, AI Observability, and AI Governance platforms.
• Good understanding of Machine Learning, NLP, Model Evaluation, Explainability, and Responsible AI concepts.
• Working knowledge of Databricks, Apache Spark, Kafka, Data Pipelines, Event-Driven Architectures, and Real-Time Data Processing.
• Experience building analytics and business applications using Power BI, Power Apps, and Power Automate.
• Familiarity with Azure DevOps, GitHub Actions, Docker, Kubernetes, Terraform, and CI/CD practices.
• Strong proficiency in Python, SQL, REST APIs, PostgreSQL, and Redis.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Engineering, or related field.
• 7+ years of overall IT experience with significant experience in AI Engineering, ModelOps, MLOps, or AI Platform leadership roles.
• Proven experience in deploying, governing, monitoring, and scaling ML and LLM-based solutions in enterprise environments.
• Strong client-facing consulting, stakeholder management, and delivery leadership experience.
• Experience leading cross-functional teams comprising AI Engineers, ML Engineers, Data Engineers, and Platform Engineers.
• BFSI or other regulated industry experience preferred.

Preferred Certifications

• Microsoft Azure AI Engineer Associate
• Azure Machine Learning
• AWS Machine Learning Specialty
• Kubernetes or Cloud Platform Certifications

Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.

Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.

Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions.

If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.

About Cognizant: 
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.