AWS AI Architect (AWS Bedrock Expertise

AWS AI Architect

Location: Miami, FL and Seattle, WA (Hybrid)

Contract

Position Overview

We are seeking an experienced AWS AI Architect with deep hands-on expertise in Amazon Bedrock to design, architect, and implement end-to-end Generative AI and LLM-powered solutions. The ideal candidate will combine strong cloud architecture skills with applied AI knowledge to build scalable, secure, enterprise-grade AI platforms and applications on AWS.

Key Responsibilities

• Design and architect Generative AI solutions using Amazon Bedrock, including model selection, orchestration, security, and deployment.
• Build Retrieval-Augmented Generation (RAG) pipelines using Amazon OpenSearch, Aurora ML Vector Engine, DynamoDB, or 3rd-party vector databases.
• Evaluate foundation models (Claude, Llama, Amazon Titan, Cohere Command) and recommend the right model per use case.
• Architect multi-agent GenAI systems using Bedrock Agents and Bedrock Knowledge Bases.
• Develop end-to-end AI workflows using Lambda, Step Functions, API Gateway, and other serverless components.

• Implement prompt engineering, prompt optimization, and evaluation frameworks.
• Customize and fine-tune LLMs through Bedrock Fine-Tuning workflows.
• Create reusable GenAI components, patterns, and accelerators for enterprise adoption.
• Integrate Bedrock with enterprise data lakes, APIs, and backend systems.

• Build scalable ingestion and preprocessing pipelines using Glue, S3, EMR, Redshift, Kinesis, etc.
• Architect secure access patterns using IAM, VPC, PrivateLink, KMS, and guardrails for responsible AI.
• Implement observability, governance, and monitoring using CloudWatch, CloudTrail, and SageMaker MLOps.

• Lead architecture reviews, technical deep dives, and PoCs across business units.
• Work closely with product, engineering, and business teams to translate needs into scalable AI solutions.
• Mentor teams on GenAI, Bedrock best practices, and AWS architecture standards.

Required Skills & Qualifications

• 7+ years of experience in cloud architecture (AWS preferred).
• 3+ years of hands-on experience in AI/ML, with at least 1–2 years in Generative AI solutions.
• Strong expertise with Amazon Bedrock (mandatory).
• Experience with major foundation models (Claude, Llama, Titan, Cohere).
• Strong command of Python, API-based integrations, and serverless application development.
• Proven experience implementing RAG architectures at scale.
• Deep understanding of cloud security, networking, and identity (IAM, KMS, VPC).
• Hands-on with vector databases and embedding strategies.
• AWS certifications preferred:
• AWS Certified Solutions Architect – Professional
• AWS Certified Machine Learning – Specialty

Preferred Qualifications

• Experience with SageMaker, EKS, or ECS for model deployment and experimentation.
• Understanding of responsible AI, content filters, and enterprise guardrails.
• Background in building enterprise copilots, chatbots, and document intelligence solutions.
• Familiarity with event-driven architectures using EventBridge.