Amazon.com Services LLC
Advertising
Sr.SoftwareDevelopmentEngineer,ConversationalAdExperiences
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr. Software Development Engineer, Conversational Ad Experiences at Amazon.com Services LLC. Skills: Large Language Models, LLMOps, Distributed systems, Conversational AI. Define architecture of conversational advertising. Lead technical vision for sponsored conversational shopping experiences”
What You'll Achieve.
Impact hundreds of millions of shoppers; Drive incremental sales; Shape revenue outcomes
Industry & Context.
Ambiguous problem definition; Undefined problem spaces; Break down complex problems
What They're Looking For.
Must Have
5+ years non-internship professional software development experience, 5+ years programming experience, 5+ years leading design or architecture experience, Experience as a mentor, Experience as a tech lead, Experience leading an engineering team
Nice to Have
5+ years full software development life cycle experience, Bachelor's degree in computer science or equivalent
What You'll Do.
Define architecture of conversational advertising
Lead technical vision for sponsored conversational shopping experiences
Own technical direction for initiatives
Design large-scale distributed systems
Build ML infrastructure
Build LLMOps pipelines
Partner with science to bring large language models
Set engineering bar for team
Ship customer-facing experiences
Own architecture decisions
Influence team's technical roadmap
Operationalize large language models
Design data processing pipelines
Pioneer new technical approaches
Raise bar for what's possible
Collaborate with cross-functional teams
Influence cross-functional teams
Integrate AI-driven solutions
Drive technical excellence
Establish engineering best practices
Break down complex problems
Shape long-term technical vision
How You'll Work.
Team & Collaboration
Cross-functional teams; Product teams; Science teams; Design teams
Process & Methodology
Problem definition, Production deployment, Actionable technical strategies, Clear milestones
Full Job Description
Define the architecture of conversational advertising powered by Large Language Models—an entirely new category that doesn't exist yet. As a Senior SDE on the CAX (Conversational Ad Experiences) team, you'll lead the technical vision for industry-first sponsored conversational shopping experiences on Amazon Search, impacting hundreds of millions of shoppers worldwide. This isn't incremental work. The CAX team is building from zero-to-one: LLM-powered ad experiences that fundamentally change how brands connect with customers in real time. As a senior engineer, you will own the technical direction for ambiguous, high-impact initiatives—designing large-scale distributed systems, building ML infrastructure and LLMOps pipelines, and partnering directly with science to bring large language models into production. You'll set the engineering bar for the team while shipping customer-facing experiences at Amazon's global scale. Why choose this role: - Greenfield + GenAI — You're not maintaining legacy systems; you're architecting industry-first conversational ad experiences from scratch - Technical leadership — Own architecture decisions, drive system design, and influence the team's technical roadmap - LLMs in production at scale — Partner with science to operationalize large language models serving hundreds of millions of shoppers - Outsized business impact — SPB drives incremental sales for millions of advertisers; your systems directly shape revenue outcomes - Ambiguity as opportunity — Undefined problem spaces where senior engineers thrive and have the most influence Key job responsibilities - Lead the design and architecture of net-new conversational ad experiences on the Amazon Search page, making critical technical decisions that define system direction - Drive major product and engineering initiatives end-to-end, from ambiguous problem definition through production deployment and operational excellence - Architect and build large-scale, low-latency distributed system
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