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Principal Generative AI Solutions Architect

Amazon Web Services, Inc.Palo Alto, California🇺🇸United StatesPosted Sep 21, 2026

Quick Overview

Seniority
Leader
Employment type
Full Time
Work mode
Hybrid
Location
Palo Alto, California, United States
MicroservicesAWSETLMLOpsMachine LearningGenerative AILLMPythonREST

Job Description

Amazon Web Services, Inc. seeks a Principal Specialist, GenAI to lead strategic adoption of generative AI on AWS. You will own end-to-end architecture for GenAI solutions, guiding customers on LLM selection, fine-tuning, prompt engineering, and secure deployment using AWS services such as Bedrock and SageMaker. Partnering with sales and product teams, you'll build prototypes, reference architectures, and best practices for large-scale, production-ready workloads. In AWS's customer-obsessed, innovative culture, you'll mentor teams, deliver workshops, and shape our GenAI roadmap while solving complex challenges for global customers.

Responsibilities

  • Design and lead Gen
  • AI solution architectures on AWS for enterprise customers
  • Partner with sales and product teams to drive adoption of AWS Gen
  • AI services
  • Build prototypes, reference architectures, and best practices for Gen
  • AI workloads
  • Advise customers on model selection, fine-tuning, prompt engineering, and evaluation
  • Ensure Gen
  • AI solutions meet security, compliance, and scalability requirements
  • Deliver technical presentations, workshops, and enablement for customers and partners
  • Contribute to thought leadership through whitepapers, blogs, and conference talks
  • Mentor engineers and specialists on Gen
  • AI patterns and tools

Required Skills

  • AWS cloud architecture (EC2, S3, IAM, VPC, Lambda)
  • AWS Gen
  • AI services (Bedrock, Sage
  • Maker, related ML services)
  • Python for ML/Gen
  • AI workloads
  • LLM fine-tuning and prompt engineering
  • Machine learning lifecycle and MLOps
  • API design and integration (REST, microservices)
  • Security, compliance, and governance on cloud
  • Data engineering for AI (ETL, feature stores, vector stores)
  • Solution architecture and systems design
  • Technical stakeholder communication and technical writing

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