Senior AI Engineering Lead – Generative AI & Strategy

Amazon Web Services (AWS)

Seattle (WA)

On-site

USD 220,000 - 298,000

Full time

32 hours ago

Be an early applicant

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Job summary

Amazon Web Services, Inc. in Seattle seeks a Sr Manager, AI Engineering to lead a world-class team of customer-facing AI Engineers and Architects who help enterprises architect and deploy AI systems to production.

You will hire, mentor, and sponsor strategic customers, translating AI strategy into architectural decisions with CAIOs and CTOs at Fortune 500 firms. Beyond direct customer engagement, you will drive Thought Leadership, partner with Bedrock and related services, and build scalable

Qualifications

10+ years of engineering experience.
5+ years of engineering team management experience.
10+ years of consumer software experience.
Experience partnering with product or program management teams.
Experience managing multiple concurrent programs in an Agile environment.

Responsibilities

Hire, develop, and retain a world-class team of Applied AI Architects, fostering a culture of technical excellence, customer obsession, and continuous learning.
Set the technical vision and strategic direction for the Applied AI Architecture practice worldwide, ensuring the team's guidance and best practices evolve with the rapidly changing generative AI landscape.
Serve as a technically credible executive sponsor to strategic customers, engaging directly with C-level technology leaders on AI strategy, production architecture, and business outcome realization.
Build and maintain trusted relationships with AWS service and product teams, establishing feedback loops that translate field insights into product improvements and roadmap influence.
Drive Thought Leadership through publications, frameworks, and speaking engagements that position AWS as the leader in production generative AI and agentic systems.
Create scalable programs, tools, and enablement assets that help the broader AWS field execute generative AI engagements with customers at scale.
Navigate ambiguity in a fast-moving technical domain, making directional decisions with incomplete information while building mechanisms to course-correct.
Represent the voice of the customer internally, synthesizing patterns across engagements to inform organizational strategy and investment priorities.