Senior GenAI Architect – Multi-Agent Systems Lead

Amazon Inc.

Seattle (WA)

On-site

USD 168,000 - 227,000

Full time

2 days ago
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Benefits offered by this job

health insurance
401(k) matching
paid time off
parental leave

Job summary

Amazon Seller Assistant is seeking a Sr. Software Development Engineer to lead the design and development of agentic software systems across the full lifecycle, owning architectural direction for multi‑agent services and guiding technology choices.

You will collaborate with scientists, engineers, and product managers to translate GenAI research into reliable seller‑facing features. You will mentor engineers, drive best practices, and contribute to team growth while evaluating AI tooling

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 of new and existing systems.

Responsibilities

  • Lead the design and development of agentic software systems across the full lifecycle — from design to deployment and maintenance.
  • Own your team's architectural direction for multi-agent services and guide technology choices.
  • Collaborate with applied scientists, partner engineering teams, and product managers to translate GenAI research into production‑grade features.
  • Mentor and coach engineers, drive engineering best practices, and contribute to team growth.

Skills

Software development
Programming languages
Architecture leadership
Mentoring

Education

Bachelor's degree in computer science

Job description

Amazon Seller Assistant is seeking a Sr. Software Development Engineer to lead the design and development of agentic software systems across the full lifecycle, owning architectural direction for multi‑agent services and guiding technology choices.

You will collaborate with scientists, engineers, and product managers to translate GenAI research into reliable seller‑facing features. You will mentor engineers, drive best practices, and contribute to team growth while evaluating AI tooling

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