Roles and Responsibilities :
Essential Skills/Experience
Enterprise Architecture experience: proven EA leadership translating concepts into production-ready solutions.
Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.
AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.
Engineering and analytics: robust Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.
Data modelling and governance: conceptual/logical modelling and governance standards in regulated settings.
Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle understanding.
Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.
Degree in data science, AI engineering,



or a related field (or equivalent experience).

Desirable Skills/Experience
Postgraduate degree in MIS, AI, data science, or a related field.
Recognised thought leader in applying AI within the enterprise and across the industry.
Extensive senior AI, data science, data engineering, and AI architecture experience delivering large-scale blueprints.
Hands-on building AI models, including LLMs and LVMs, across diverse data types.
Agile AI delivery experience; tools for metadata cataloguing, data modelling, and enterprise architecture.
Experience in the pharmaceutical AI industry.
Ability to simplify the enterprise landscape and reduce technology debt.

📌 Enterprise Architect Bengaluru
🏢 Virtusa
📍 Bengaluru