AWS GenAI Solutions Architect

• AWS GenAI Stack – Hands-On
  
  • Strong hands-on experience with Amazon Bedrock, including selecting appropriate foundation models and explaining the rationale for model selection.
  • Amazon OpenSearch for vector search and semantic retrieval.
  • Amazon S3 for data/document storage.
  • Amazon Bedrock AgentCore / Agent Core — actual production deployment experience is required; conceptual knowledge is not sufficient.

• RAG & Agentic Architecture
  
  • Design and implementation of RAG (Retrieval-Augmented Generation) solutions with grounded, cited responses.
  • Agentic architectures, including short-term and long-term agent memory.
  • Experience implementing human-in-the-loop workflows and approval patterns.
  • Data Ingestion & Document Processing — Critical
  • Hands-on ownership of ingestion pipelines processing millions of mixed-format documents.
  • Experience with PDFs containing tables/images, CSVs, and other unstructured/semi-structured data.
  • Strong understanding of document extraction, parsing, preprocessing, chunking, metadata and embedding strategies.
  • Candidate must be able to architect and own the ingestion/data pipeline, rather than relying on a separate data engineering team.

• Semantic Layer & Data Architecture
  
  • Experience architecting a semantic layer across structured and unstructured data.
  • Ability to model and integrate different data shapes for GenAI/RAG applications.

• AWS Platform & Infrastructure
  
  • EKS / Kubernetes and container architecture.
  • Ability to explain and defend EKS vs. ECS architecture decisions.
  • Strong Terraform / Infrastructure-as-Code experience through production deployment.
  • AWS networking, monitoring, logging and production infrastructure.

• Security & Governance – Regulated Data
  
  • Strong understanding of AWS security architecture, including:
    
    • IAM / least-privilege access
  • • KMS
  • • TLS / encryption
  • • Private networking / VPC
  • • Secrets Manager
  • • Bedrock Guardrails
  • • Prompt-injection defense
  • • PII detection/masking
  • • CloudTrail / CloudWatch
• 
  
  • Experience designing GenAI solutions for regulated or sensitive data environments.
• Programming
  
  • Strong Python skills; able to develop and troubleshoot production-quality GenAI/data pipeline components.
• Architecture & Client Communication
  
  • Experience creating Architecture Decision Records (ADRs) and technical architecture documentation.
• • Ability to present, explain and defend architecture decisions to client architecture review boards and senior technical stakeholders

Who We Are

• • We connect thoughtfully curated talent with reputable employers in our field.
• • We partner with like-minded companies to bolster mutual success and understanding.
• • We deliver results through strategic planning and meticulous project management.

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