Description

You will design end-to-end AI/ML architectures covering data ingestion, feature engineering, model development, deployment, monitoring, and retraining.

Responsibilities

• Define enterprise AI reference architectures for GenAI, ML, NLP, computer vision, and predictive analytics use cases.
• Select and standardize AI platforms, frameworks, and tools including cloud AI services, MLOps platforms, and LLM frameworks.
• Partner with business, data, and engineering leaders to translate use cases into technical AI solutions.
• Guide AI adoption across ETL, data platforms, and analytics ecosystems.
• Support proof of concepts and pilots for AI initiatives.

Required Skills

• 8+ years of experience in data, analytics, or platform architecture roles.
• 4+ years of experience designing and implementing AI/ML solutions at scale, deployed to production.
• Strong knowledge of Machine Learning, Deep Learning, and Generative AI concepts.
• Proficiency in Python and SQL.
• Experience with cloud AI platforms (Azure, AWS, GCP).
• Familiarity with MLOps tools and data engineering practices.
• Understanding of APIs, microservices, containers, and orchestration.

Preferred Skills

Key Skills

Education

Any Graduate