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Cognizant
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Unknown · São Paulo, Brazil
31 open roles4 posted in 7d31 in 30d
Work-life balance 4.4Compensation & benefits 4.3Culture & values 4.3
Hiring: Engineering
What employees say
+ Initiative the works to develop technical knowledge
− There is no time consumption
More reviews on the company profile.
Interview experience · Jr.Software Engineer
1)2Technical round (Based on Technical Skill ,Two Coding based Question,SQL) 2)Hr discussion (if selected ) Cognizant helps companies modernize technology, reimagine processes and transform experiences so they stay ahe
Average difficulty · India · 3 reports
More interview insightsJob description
Overview
We are seeking an experienced ModelOps Lead to drive enterprise-scale AI, Generative AI, and ModelOps initiatives across Machine Learning and LLM platforms.
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.
Qualifications
- 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.
- 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.
- Microsoft Azure AI Engineer Associate
- Azure Machine Learning
- AWS Machine Learning Specialty
- Kubernetes or Cloud Platform Certifications
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Job application FAQ
Last updated 26 October 2026
- How do I apply for Manager-Data & ML Engg at Cognizant?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Cognizant may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Manager-Data & ML Engg role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Manager-Data & ML Engg remote or on-site in Chennai, Tamil Nadu?
- This listing is marked on_site with location Chennai, Tamil Nadu. Confirm details on the job description before applying.
- What skills matter for this Manager-Data & ML Engg role at Cognizant?
- Key skills for this role include skills listed in the job description. Upload a resume to see which requirements you already meet and which are gaps.