Description

You will design and architect Generative AI solutions on AWS, focusing on Amazon Bedrock, RAG pipelines, and multi-agent systems. You own the end-to-end lifecycle from model selection and fine-tuning to secure deployment and observability.

Responsibilities

• Architect and implement Generative AI solutions using Amazon Bedrock, including model selection, orchestration, and security.
• Build scalable Retrieval-Augmented Generation (RAG) pipelines using Amazon OpenSearch, Aurora ML Vector Engine, or DynamoDB.
• Develop end-to-end AI workflows using Lambda, Step Functions, and API Gateway.
• Implement prompt engineering, evaluation frameworks, and fine-tuning workflows for foundation models.
• Lead architecture reviews and mentor teams on GenAI best practices and AWS standards.

Required Skills

• 7+ years of cloud architecture experience, with a strong preference for AWS.
• 3+ years in AI/ML, including 1–2 years specifically with Generative AI solutions.
• Mandatory deep expertise with Amazon Bedrock.
• Proven experience implementing RAG architectures at scale.
• Strong command of Python and API-based integrations.
• Hands-on experience with vector databases and embedding strategies.
• Deep understanding of cloud security, networking, and identity (IAM, KMS, VPC).
• Experience integrating Bedrock with enterprise data lakes, APIs, and backend systems.

Preferred Skills

• AWS certifications: Solutions Architect – Professional or Machine Learning – Specialty.
• Experience with SageMaker, EKS, or ECS for model deployment.
• Familiarity with event-driven architectures using EventBridge.

Key Skills

Education

Not specified