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Principal Solutions Architect, AI-Driven Guidance, Well-Architected Solutions Innovation

Job in Irvine, Orange County, California, 92713, USA
Listing for: Amazon
Full Time position
Listed on 2026-06-02
Job specializations:
  • IT/Tech
    AI Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Description

Do you want to set the standard for how builders architect AI workloads that are secure, reliable, and efficient on AWS? We are looking for a Principal Solutions Architect with deep expertise in Machine Learning, Generative AI, and Agentic AI to own and drive the strategic vision for Architectural Guidance Best Practices across AI workloads. You will operate at the intersection of AI technologies and cloud architecture, ensuring AI workloads achieve Well-Architected outcomes across all six pillars — Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability — influencing both internal AWS teams and the broader builder community.

In this role, you will define the long-term technical direction for AI architectural guidance, translate emerging AI/ML patterns into prescriptive and actionable best practices grounded in the Well-Architected pillars, and influence AWS service design to better serve AI builders worldwide.

Key job responsibilities
  • Set Strategic Technical Direction:
    Define and own the long-term vision and roadmap for AI/ML architectural guidance aligned to the AWS Well-Architected Guidance pillars.
  • Generative AI & Agentic AI Thought Leadership:
    Serve as the organization's principal technical authority on architectures involving foundation models, retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering, agentic workflows, multi-agent orchestration, and responsible AI practices. Drive consensus on complex, ambiguous technical decisions.
  • Raise the Bar Across the Organization:
    Establish quality standards, review mechanisms, and architectural guardrails that elevate the entire guidance portfolio. Define what "great" looks like and hold the team accountable.
  • Influence Service Roadmaps:
    Partner with Stakeholders and Engineers across AWS service teams (Amazon Bedrock, Sage Maker, Q, etc.) to represent the customer voice, validate architectural recommendations, and influence product direction based on patterns observed in production AI workloads.
  • Executive Customer Engagement:
    Engage directly with strategic enterprise customers to validate guidance through real-world implementations, identify emerging architectural challenges, and translate insights into scalable best practices.
  • Drive Innovation in Content Delivery:
    Own the strategy for automation tooling and pipelines (including Generative AI–assisted authoring) that accelerate the creation, review, and publication of guidance ine mechanisms that ensure guidance remains current as the AI landscape evolves rapidly.
  • External Thought Leadership:
    Publish whitepapers, blog posts, and reference architectures; present at AWS events (re:

    Invent, Summits, webinars) and industry conferences to establish AWS as the definitive authority on Well-Architected AI.
  • Mentorship & Organizational Impact:
    Mentor senior architects, drive hiring bar-raising, and build a community of practice that scales AI/ML architectural expertise across the organization. Contribute to organizational strategy and workforce planning.
  • Mechanisms & Operational Excellence:
    Design and implement repeatable mechanisms (e.g., architectural review processes, guidance lifecycle management, feedback loops) that ensure sustained quality and relevance at scale.
  • Hands-On Technical Validation:
    Validate architectural recommendations through prototyping, proof-of-concept implementations, and code samples that demonstrate best practices in practice.
Basic Qualifications
  • Bachelor's degree in computer science, engineering, mathematics or equivalent
  • 10+ years of cloud architecture and solution implementation experience, or degree in advanced technology
  • 7+ years of hands‑on experience designing, building, or advising on Machine Learning and/or AI systems in production environments
  • Deep understanding of the end-to-end ML lifecycle: data preparation, model training, evaluation, deployment, monitoring, and governance
  • Demonstrated ability to influence technical direction across organizational boundaries without direct authority
  • Exceptional written and verbal communication skills with a track record of publishing authoritative technical…
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