21 hours ago
Chennai, IndiaStaff+
Responsibilities
- Lead architecture design for products and capabilities across NIQ platforms.
- Define high-level solution approaches, blueprints, reference architectures, principles, standards, patterns, and architecture decision records.
- 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 on confidentiality, intellectual property, regulatory compliance, transparency, and risk management.
- Evaluate front-end applications, platform services, data pipelines, databases, AI platforms, foundation models, vector stores, and agentic frameworks, including build-versus-buy decisions.
- Establish evaluation criteria for quality, accuracy, groundedness, safety, latency, scalability, resilience, and total cost of ownership.
- Drive innovation through proofs of concept, technology migrations, controlled pilots, and productionization.
- Provide architecture leadership, coaching, and design governance across teams.
Requirements
- 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 with a strong engineering background and enterprise-scale platform experience.
- Experience designing and delivering scalable, secure, highly available, and observable distributed systems in production.
- Strong knowledge of enterprise data architecture, data modeling, and high-volume processing across relational and non-relational data stores; multi-terabyte database experience 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 with Responsible AI governance, AI risk controls, threat modeling, 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.
- Knowledge of cloud architecture, preferably Microsoft Azure, including identity, networking, security, data, integration, monitoring, and platform services.
- Practical experience architecting or delivering production AI or generative AI solutions involving large language models, embeddings, vector search, retrieval-augmented generation, prompt and context engineering, and model evaluation.
- Understanding of agentic AI patterns including orchestration, planning and reasoning workflows, tool calling, state and memory management, multi-agent coordination, human oversight, and safe execution boundaries.
- Ability to communicate architecture decisions to technical and non-technical stakeholders and influence outcomes across organizational boundaries.
Benefits
- Flexible working environment.
- Volunteer time off.
- LinkedIn Learning.
- Employee Assistance Program (EAP).