The architect will design and implement end-to-end GenAI solutions, including RAG architectures and data ingestion pipelines. They are responsible for owning the technical architecture, ensuring production-grade deployment, and communicating decisions to senior stakeholders.
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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