Description

You will design and architect enterprise-grade AI solutions leveraging Generative AI and Large Language Models. You own the full lifecycle from solution design to production deployment and governance.

Responsibilities

• Define architecture for LLM-based systems, agentic workflows, RAG, and AI copilots.
• Evaluate and select models, frameworks, and infrastructure for production AI systems.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Implement frameworks for AI governance, model explainability, transparency, and risk management.
• Act as a trusted technical advisor to clients, translating business problems into AI-driven solutions.

Required Skills

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• 5+ years of experience designing and deploying AI/ML systems in production.
• Deep knowledge of Large Language Models (LLMs) and Generative AI architectures.
• Strong expertise in Machine Learning fundamentals and ML pipelines.
• Experience with MLOps and model lifecycle management.
• Proven experience in AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.
• Ability to communicate complex AI concepts to executives and engineering teams.

Preferred Skills

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems and AI platform engineering.
• Contributions to AI research, open-source projects, or technical publications.

Key Skills

Education

Master's degree