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AWS GenAI / Solutions Architect

High Bridge ConsultingUnited States🇺🇸United StatesPosted Oct 8, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
22 hours ago
AWSEncryptionData PipelineKubernetesPythonTerraform

Job Description

Our client is high end Management Consulting firm and a major AWS partner. We are looking to hire on a Full-Time basis an 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

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