Principal Platform Architect | Agentic AI
Role Overview
Define architecture for key capabilities across NielsenIQ's global data platform.
Partner with product, operations, architecture, engineering, and development teams from requirements through production operation.
Shape responsible adoption of artificial intelligence, generative AI, and agentic AI across the enterprise.
Grow into an end-to-end platform architect as knowledge of NielsenIQ platforms expands.
Key Skills for This Role
Full Job Posting
Role overview
Define architecture for key capabilities across NielsenIQ's global data platform.
Partner with product, operations, architecture, engineering, and development teams from requirements through production operation.
Shape responsible adoption of artificial intelligence, generative AI, and agentic AI across the enterprise.
Grow into an end-to-end platform architect as knowledge of NielsenIQ platforms expands.
Architecture responsibilities
- Lead architecture designs for products and capabilities across NielsenIQ platforms.
- Define solution approaches and blueprints for component design, platform integration, and technology roadmaps.
- Maintain reference architectures, principles, standards, patterns, and architecture decision records.
- Shape enterprise architecture for AI, generative AI, and agentic AI solutions.
- Define secure and scalable AI-agent patterns covering access, grounding, guardrails, evaluation, observability, and cost.
- Partner with security, privacy, legal, data governance, and Responsible AI stakeholders.
- Assess emerging technologies and build-versus-buy alternatives.
- Establish evaluation criteria for AI and platform solutions.
- Drive proofs of concept, migrations, controlled pilots, and productionization.
- Provide architecture leadership, coaching, and design governance.
Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
- At least 8 years of application development, solution design, or software architecture experience.
- Experience delivering scalable, secure, highly available, and observable distributed systems in production.
- Strong enterprise data architecture, data modelling, and high-volume data processing knowledge.
- Experience with Azure AI services, Azure AI Foundry, Azure OpenAI, or comparable platforms.
- Familiarity with agentic AI frameworks and interoperability standards.
- Experience with Responsible AI governance, AI risk controls, threat modelling, red-teaming, or AI security patterns.
- Strong knowledge of data structures, algorithms, and non-functional system design.
- Production experience with AI or generative AI, including LLMs, embeddings, vector search, RAG, and model evaluation.
- Understanding of agent orchestration, tool calling, memory, multi-agent coordination, human oversight, and safe execution.
- Ability to communicate architecture decisions and influence stakeholders across organizational boundaries.
Work arrangement
- The role is described in source metadata as hybrid in Chennai.
Benefits
- Flexible working environment, volunteer time off, LinkedIn Learning, and an employee assistance program are listed.
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