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

Description

The role is in Chennai, on the identity and access management (IAM) program of the company, a consumer intelligence firm with operations in more than 100 markets, covering over 90% of the world's population.

The company is adding AI and machine learning to its enterprise identity and access setup to strengthen security, automate work and improve the user experience at scale.

You will be a senior hands-on engineer who designs and builds machine learning systems in complex, distributed, cloud-based environments, with real technical ownership and influence over architecture.

You will work closely with the cybersecurity, engineering and AI teams on identity, access and security intelligence solutions.

The ideal person is a self-driven problem solver who likes working where AI/ML, cybersecurity, cloud platforms and automation meet, and who wants to help grow the company's global IAM program.

Responsibilities

• Lead the design and evolution of the IAM technology stack, keeping architecture, implementation, monitoring, maintenance and enhancements to top-tier security standards.
• Design, build and evolve AI/ML solutions that analyse identity, access and behavioural data to spot anomalies, lower risk and automate identity security services that enforce IAM, PAM and secrets management controls.
• Own the full ML lifecycle, from data ingestion and feature engineering through model development, evaluation, deployment, monitoring and ongoing improvement.
• Architect and implement scalable ML pipelines using Python, cloud-native services, APIs and infrastructure-as-code.
• Work with cybersecurity and other engineering teams to bring ML models into enterprise IAM, PAM and secrets management workflows, helping shape the roadmap and drive wide adoption and enforcement.
• Apply advanced security engineering principles to analyse, design, build, deploy and support complex software and infrastructure upgrades, and set best-practice standards.
• Build and deploy real-time and batch inference services that recognise identity and access patterns.
• Apply advanced ML methods such as anomaly detection, clustering, classification and graph-based models to human and non-human identity use cases.
• Design model monitoring, drift detection and performance metrics tied to security KPIs and business outcomes.
• Use Azure, AWS or GCP for distributed training, model serving and data processing.
• Drive adoption of MLOps practices, including CI/CD for models, versioning, reproducibility and observability.
• Work with product owners and stakeholders to turn security problems into well-defined ML use cases.
• Explain technical concepts, trade-offs and results clearly to both technical and non-technical audiences.
• Mentor junior engineers and help set cybersecurity engineering standards for applied AI across the organisation.

Requirements

• A bachelor's degree in cybersecurity, computer science, computer information systems, data science or a related field. A master's is preferred.
• 7+ years of software engineering experience, including 4+ years architecting and designing AI/ML systems at global scale. Cybersecurity experience is preferred.
• Strong Python skills and experience building ML systems with frameworks such as PyTorch, TensorFlow or scikit-learn.
• Hands-on experience with data pipelines, APIs and distributed systems.
• Broad knowledge of IAM capabilities, identity stores, authentication and authorisation, strong authentication, privileged access methods and Zero Trust principles.
• Experience deploying and running ML models in Azure, AWS or GCP.
• Practical knowledge of MLOps, including model versioning, CI/CD, monitoring and automation.
• Experience with identity, security or behavioural data such as IAM records, access logs or telemetry.
• Familiarity with REST APIs, Git-based workflows, containerisation and infrastructure-as-code.
• Understanding of non-human identities, service accounts, secrets and automation-driven access is a strong plus.
• You can design solutions that balance accuracy, scalability, explainability and operational reliability.
• Strong analytical thinking and problem-solving in ambiguous, real-world settings.
• Excellent verbal and written communication, with the ability to influence cross-functional teams.
• You work independently and drive complex initiatives across large organisations.
• You can prioritise and carry out tasks in a fast-moving setting, balancing risk reduction with business goals.
• You translate complex technical ideas into clear, actionable insights for varied stakeholders.
• You have a proven record of driving adoption of security best practices across large organisations.

Conditions

The work is in Chennai.

Flexible working environment.

Equal opportunity: the company values diversity, equity and inclusion.

The company may use AI tools in recruitment, including résumé screening, assessments and scheduling, with final hiring decisions made by people. Accommodation requests go to the local HR representative.

Benefits

• Flexible working environment.
• Volunteer time off.
• LinkedIn Learning access.
• Employee assistance programme (EAP).