AWS GenAI Solutions Architect

HIGH BRIDGE CONSULTING LLC

United States

Remote

USD 180,000 - 240,000

Full time

26 hours ago
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Job summary

HIGH BRIDGE CONSULTING LLC is hiring an AWS GenAI / Solutions Architect for a fully remote, full-time role. The candidate will own ingestion pipelines, design RAG architectures with grounded responses, and architect a semantic layer across mixed data sources.

The role requires hands-on Bedrock, AgentCore, Terraform, Kubernetes, and Python experience, plus the ability to communicate architecture decisions to senior stakeholders.

Qualifications

  • Extensive hands-on AWS GenAI/RAG architecture and deployment experience.
  • Proven ability to own ingestion pipelines for millions of documents.
  • Strong Python and production-quality data pipeline development skills.
  • Ability to present complex architecture to clients and governance boards.

Responsibilities

  • Architect and own the ingestion/data pipeline from PDFs, CSVs, and other formats.
  • Design RAG solutions with grounded, cited responses and agent memory.
  • Develop a semantic data layer across structured/unstructured data.
  • Lead client communications and ADRs documenting architecture decisions.

Skills

AWS Bedrock
OpenSearch
S3 storage
Bedrock AgentCore
RAG architecture
Agentic memory
Human-in-the-loop
Document ingestion
Python
ADR / architecture docs
EKS / Kubernetes
Terraform
Security & governance

Tools

Terraform
Kubernetes (EKS)
CI/CD tooling

Job description

Our client is a 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.

This is a remote position.

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