Role & responsibilities

- Define end-to-end enterprise AI architecture for scalable, secure, and responsible GenAI products leveraging LLMs, RAG, multi-agent systems, and knowledge-driven pipelines.
- Architect enterprise-grade AI platforms spanning data, model, agent orchestration, APIs, and product integration across cloud-native ecosystems (Azure/AWS).
- Design advanced retrieval ecosystems (vector DBs, knowledge graphs, hybrid search) to maximize contextual accuracy and minimize hallucinations.
- Lead development of production-ready AI products with robust MLOps, observability, governance, evaluation frameworks, and continuous feedback loops.
- Establish AI reference architectures, reusable frameworks, and engineering standards for product teams to accelerate delivery at scale.
- Drive integration of structured domain knowledge (ontologies, taxonomies,



semantic layers) into AI solutions for domain-specific intelligence.
- Own AI platform strategy including model selection (open/closed), fine-tuning, prompt engineering, cost optimization, and performance benchmarking.
- Ensure Responsible AI practices covering security, compliance, explainability, risk mitigation, and data privacy for enterprise deployments.
- Collaborate with product, engineering, business, and leadership stakeholders to translate customer pain points into scalable AI-led solutions.
- Mentor teams and drive AI adoption, innovation roadmap, and enterprise-wide transformation towards AI-first product engineering.

📌 Artificial Intelligence Architect (Chennai)
🏢 Sunovaa Tech
📍 Chennai