Senior AI Production Architect (FDE)

Amazon Inc.

Bellevue (WA)

On-site

USD 168,000 - 227,000

Full time

14 days+

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Job summary

Amazon is seeking a Forward Deployed Engineer to embed with enterprise customers, designing, building, and running AI-powered production systems. You will own outcomes end-to-end from prototype to enterprise-scale deployment, producing production-grade software and reusable architectures.

You will lead technical delivery across engagements, drive architecture decisions across services, and align with the customer’s long-term strategy.

Qualifications

5+ years of non-internship professional software development experience.
5+ years of programming with at least one software programming language experience.
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
Experience as a mentor, tech lead or leading an engineering team.
Experience communicating technical concepts to both technical and non-technical audiences, including senior stakeholders.
Experience leading agentic and spec-driven development at production scale (developing AI agents a plus).
Experience with AI tools: eval frameworks, agent tooling, RAG pipelines, and prompt engineering.

Responsibilities

Lead technical delivery across customer engagements. Own the technical strategy and execution for complex, multi-workstream customer AI programs.
Make architecture decisions that span multiple services and organizational boundaries.
Align technical approach with the customer's long-term technology strategy.
Requires 30–50% travel.
Architect and build production AI systems at scale. Design the foundational architectures — multi-agent orchestration, enterprise retrieval systems, decision intelligence platforms.
Drive clarity where neither the business problem nor technology approach is fully defined.
Build production systems that handle enterprise-scale traffic and reliability requirements.
Own production excellence across workstreams. Define operational standards, evaluation frameworks, and production readiness criteria for AI systems.
Establish mechanisms (testing strategies, observability standards, incident response playbooks) to ensure AI systems remain healthy.
Drive operational improvements that raise the bar for the team.
Scale the team's effectiveness. Define engineering patterns, contribute to the interview and hiring process, and mentor junior FDEs into independent contributors.
Coach others on system design, customer engagement, and production operations.
Drive engineering excellence standards within your scope.
Accelerate customer transformation. Identify systemic opportunities to expand AI adoption across the customer organization.
Create accelerators and reusable platforms that reduce time-to-value from months to weeks.
Feed learnings back into AWS services and the FDE practice.