Location: San Antonio, TX (Onsite)
In-person interview mandatory
Role Summary
We are seeking a Senior AWS Solutions Architect – GenAI with deep expertise in Amazon Bedrock (including AgentCore) and strong capability in data engineering and AI data pipelines. This role will design and lead enterprise-grade GenAI solutions, ensuring robust architecture across AI, data, security, scalability, and operations.
Key Responsibilities
GenAI & Architecture
• Design end-to-end GenAI architectures using Amazon Bedrock and AgentCore
• Architect multi-agent workflows using Bedrock Agents, tools, guardrails, and orchestration patterns
• Design enterprise-grade architectures covering security, IAM, networking, observability, scalability, and cost optimization
• Lead architecture decisions for RAG systems, knowledge bases, embeddings, and evaluation pipelines
• Guide teams on ETL/ELT patterns and integration with AI workflows
AWS Platform & Integration
• Architect integrations using Lambda, API Gateway, VPC, IAM, S3, DynamoDB, OpenSearch, CloudWatch
• Design event-driven and microservices-based architectures
• Conduct architecture reviews, technical workshops, and stakeholder design sessions
• Act as technical advisor to senior client stakeholders
Required Skills & Experience
• 8+ years of experience in cloud architecture (strong AWS focus)
• Hands-on experience with Amazon Bedrock, including:
o Bedrock Agents
o Bedrock AgentCore
o Knowledge Bases
o Guardrails
o Tool orchestration
• Strong understanding of GenAI design patterns:
o RAG
o Agent orchestration
o Prompt engineering
o Evaluation and monitoring
• Solid experience with data engineering concepts, including:
o Data pipelines
o ETL/ELT design
o Data lake architectures
o Schema design
o Data governance
• Strong AWS service experience across:
o Lambda, API Gateway, S3, DynamoDB, OpenSearch
o Glue, Step Functions, EventBridge
o VPC, IAM, CloudWatch, CloudTrail
Preferred Qualifications
• AWS Solutions Architect Professional or relevant AWS certifications
• Experience with Python for full stack applications
• Experience with OpenSearch vector search or similar technologies
• Exposure to MLOps concepts (monitoring, evaluation, lifecycle management)
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