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

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.

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