Description

You will design and architect scalable, secure, and cost-optimized solutions on AWS, leading end-to-end design for Generative AI and Agentic AI use cases.

This role is hybrid.

Responsibilities

• Architect and implement LLM-based systems including RAG, agents, orchestration, and prompt engineering.
• Design multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, and AutoGen.
• Build and deploy ML pipelines for training, inference, monitoring, and optimization.
• Guide teams on cloud architecture patterns and AI governance.

Required Skills

• 10+ years of experience with AWS services (Lambda, EC2, ECS/EKS, S3, RDS, DynamoDB, VPC, IAM, CloudWatch).
• Hands-on experience with Generative AI and LLMs (OpenAI, Anthropic, Bedrock, Azure OpenAI).
• Experience designing Agentic AI systems (multi-agent orchestration, tool calling, memory, planning).
• Strong understanding of RAG architectures and vector databases (Pinecone, FAISS, Chroma).
• Infrastructure as Code using Terraform, CloudFormation, or CDK.
• Experience designing microservices, serverless, and event-driven architectures.
• Strong fundamentals in Machine Learning concepts and algorithms.
• Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn).

Preferred Skills

• AWS certifications (Solutions Architect – Associate/Professional).
• Experience with Amazon Bedrock.

Key Skills

Education

Bachelor’s degree