Principal Architect | Agentic AI

Responsibilities

•  Lead the development of architecture designs for key products and capabilities across NIQ platforms, working closely with product stakeholders, engineering teams, and other architects.

•  Define high-level solution approaches and blueprints that guide component-level design while maintaining an end-to-end view of platform integration, future products, and the technology roadmap.

•  Create, maintain, and promote reference architectures, architecture principles, standards, patterns, and decision records for key areas of the platform.

•  Shape enterprise architecture for AI, Generative AI, and agentic AI solutions, including model integration, retrieval-augmented generation, orchestration, tool and API use, memory, workflow automation, and human-in-the-loop controls.

•  Define reusable patterns for secure and scalable AI agents, including identity and access control, data grounding, context management, guardrails, evaluation, observability, auditability, failure handling, and cost management.

•  Partner with security, privacy, legal, data governance, and Responsible AI stakeholders to ensure AI solutions meet enterprise requirements for confidentiality, intellectual property, regulatory compliance, transparency, and risk management.

•  Assess emerging technologies and viable alternatives for front-end applications, platform services, data pipelines, databases, AI platforms, foundation models, vector stores, and agentic frameworks, including build-versus-buy recommendations.

•  Establish model and solution evaluation criteria covering quality, accuracy, groundedness, safety, latency, scalability, resilience, and total cost of ownership.

•  Identify future-state solutions and drive innovation through proofs of concept, technology migrations, controlled pilots, and productionization.

•  Provide architecture leadership, coaching, and design governance, promoting pragmatic, high-quality solutions and consistent engineering practices across teams.

• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• 8+ years of experience in application development, solution design, or software architecture, supported by a strong engineering background and experience with enterprise-scale platforms.
• Demonstrated experience designing and delivering scalable, secure, highly available, and observable distributed systems in production.
• Strong knowledge of enterprise data architecture, data modelling, and high-volume processing across relational and non-relational data stores; experience with multi-terabyte databases is strongly preferred.
• Experience with Azure AI services, Azure AI Foundry, Azure OpenAI, or comparable enterprise AI platforms.
• Familiarity with agentic AI frameworks and interoperability standards, such as semantic orchestration frameworks, multi-agent frameworks, and the Model Context Protocol.
• Experience defining Responsible AI governance, AI risk controls, threat modelling, red-teaming, or security patterns for AI-enabled applications.
• Strong knowledge of data structures, algorithms, and design for performance, scalability, availability, resilience, privacy, and security.
• Good knowledge of cloud architecture, preferably Microsoft Azure, including identity, networking, security, data, integration, monitoring, and platform services.
• Practical experience architecting or delivering AI or Generative AI solutions in production, with an understanding of large language models, embeddings, vector search, retrieval-augmented generation, prompt and context engineering, and model evaluation.
• Understanding of agentic AI architecture patterns, including agent orchestration, planning and reasoning workflows, tool calling, state and memory management, multi-agent coordination, human oversight, and safe execution boundaries.
• Ability to communicate complex architecture decisions clearly to technical and non-technical stakeholders and to influence outcomes across organizational boundaries.