Senior Engineer, IAM with designing and architecturing AI/ML systems

Senior Engineer, IAM with designing and architecturing AI/ML systems

Job Description

Senior Engineer, IAM, Chennai

NielsenIQ is looking for an individual who can join our Identity and Access Management (IAM) Program. We are evolving our enterprise Identity and Access ecosystem by embedding AI and machine learning to improve security posture, automation, and user experience at scale. To support this effort, we are seeking a Senior AI/ML Engineer with strong experience in architecting, designing, building, and operationalizing machine learning systems in complex, distributed, and cloud-based environments. 
In this role, you will lead the development of AI-driven identity, access, and security intelligence solutions, working closely with Cybersecurity, Engineering, and AI teams. You will be responsible for designing ML architectures, building production-grade pipelines, deploying models at scale, and driving measurable outcomes through applied AI for supporting out Identity Security initiative. This is a hands-on Senior Engineering role with significant technical ownership and architectural influence. 
The ideal candidate is a self-driven problem solver who enjoys working at the intersection of AI/ML, Cybersecurity, Cloud platforms, and automation, and who wants to be part of growing NIQ global IAM program. 

Responsibilities:

• Lead the design and evolution of the IAM technology stack, ensuring adherence to top-tier security practices across architecture, implementation, monitoring, maintenance, and enhancements. 
• Design, build, and evolve AI/ML solutions that analyze identity, access, and behavioral data to detect anomalies, reduce risk, and automate identity security services to enforce IAM, PAM and Secrets Management controls. 
• Lead the end-to-end ML lifecycle: data ingestion, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement. 
• Architect and implement scalable ML pipelines using Python, cloud-native services, APIs, and infrastructure-as-code. 
• Partner with Cybersecurity and other Engineering teams to integrate ML models into enterprise IAM, PAM, and Secrets Management workflows and drive roadmap decisions and enterprise-scale adoption and enforcement. 
• Apply advanced security engineering principles to analyze, design, develop, deploy, and support complex software solutions and infrastructure upgrades, setting standards for best practices. 
• Develop and deploy real-time and batch inference services for identity and access pattern recognition. 
• Apply advanced ML techniques (anomaly detection, clustering, classification, graph-based models, etc.,) to human and non-human identity use cases. 
• Design model monitoring, drift detection, and performance metrics aligned to security KPIs and business outcomes. 
• Leverage cloud platforms (Azure, AWS, GCP) for distributed training, model serving, and data processing. 
• Drive the adoption of MLOps best practices, including CI/CD for models, versioning, reproducibility, and observability. 
• Collaborate with product owners and stakeholders to translate security problems into well-defined ML use cases. 
• Communicate technical concepts, trade-offs, and results clearly to both technical and non-technical audiences. 
• Mentor junior engineers and help establish Cybersecurity engineering standards for applied AI across the organization. 

Qualifications

• Bachelor’s degree in Cybersecurity, Computer science, Computer Information Systems, Data Science, or a related field (Master’s preferred). 
• 7+ years of software engineering experience, with 4+ years focused on architecting and designing AI/ML systems at global scale (Cybersecurity preferred). 
• Strong proficiency in Python and experience building ML systems using modern frameworks (e.g., PyTorch, TensorFlow, scikit-learn). 
• Hands-on experience with data pipelines, APIs, and distributed systems. 
• Broad knowledge of IAM capabilities, identity stores, authentication/authorization, strong authentication, privileged access methodologies, and Zero Trust principles 
• Experience deploying and operating ML models in cloud environments (Azure, AWS, GCP). 
• Practical knowledge of MLOps practices, including model versioning, CI/CD, monitoring, and automation. 
• Experience working with identity, security, or behavioral data (IAM, access logs, telemetry, or similar domains). 
• Familiarity with REST APIs, Git-based workflows, containerization, and infrastructure-as-code. 
• Understanding of non-human identities, service accounts, secrets, and automation-driven access patterns is a strong plus. 
• Ability to design solutions that balance accuracy, scalability, explainability, and operational reliability. 
• Strong analytical thinking and problem-solving skills in ambiguous, real-world environments. 
• Excellent verbal and written communication skills, with the ability to influence cross-functional teams. 
• Proven ability to work independently while driving complex initiatives across large organizations. 
• Ability to effectively prioritize and execute tasks in a fast-paced environment, balancing risk reduction with business objectives. 
• Exceptional verbal and written communication skills, capable of translating complex technical concepts into clear, actionable insights for diverse stakeholders. 
• Strong ability to work autonomously while influencing cross-functional teams and have proven track record of driving adoption of security best practices across large organizations. 

Additional Information

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence.  All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

Experience Level

Senior Level