Description

Design and implement enterprise-scale generative AI and LLM solutions across AWS and Azure cloud environments.

This role is on-site.

Responsibilities

• Architect end-to-end GenAI systems using RAG, embeddings, prompt engineering, and agentic workflows.
• Build integrations using MCP, APIs, and microservices for enterprise applications.
• Implement MLOps/LLMOps pipelines for model lifecycle management, security, and responsible AI practices.
• Engage with senior stakeholders to define non-functional requirements including scalability, performance, and cost.

Required Skills

• 20+ years of overall IT experience with 3+ years in AI/ML/GenAI solutioning.
• Hands-on expertise with AWS Bedrock and Azure OpenAI platforms.
• Proficiency in open-source frameworks: LangChain, LlamaIndex, LangGraph, and CrewAI.
• Strong cloud architecture background in AWS and Azure.
• Experience with vector databases, data engineering, and structured/unstructured data platforms.
• Knowledge of DevSecOps, Agile delivery, and enterprise integration patterns.

Preferred Skills

• Experience designing AI copilots or workflow automation systems.
• Proven leadership and mentoring capabilities in technical teams.

Key Skills

Education

Any Gradute