Software Development Engineer III, Prime Video Personalization & Discovery

AI in this role

Build conversational AI-powered content discovery experiences combining large language models with personalization at scale.

llms

natural-language-understandingrecommendation-systemsdistributed-systemsinference-optimizationmachine-learning

Prime Video Personalization and Discovery (PVPD) is seeking a Senior Software Development Engineer to join a small, high-caliber team building the next generation of Prime Video's AI-powered content discovery experience. We are reinventing how customers find something to watch: instead of browsing and scrolling, customers tell Prime Video what they're in the mood for, through natural language conversation, personalized prompts, and interactive recommendations woven directly into the product. You'll work alongside a hand-picked group of senior engineers and applied scientists, each bringing deep expertise in their domain, moving fast on a high-visibility initiative with significant ambiguity. You'll own your area of the system end-to-end: designing, building, and operating the services that combine large language models with Prime Video's personalization, catalog, and engagement signals to deliver conversational discovery at massive scale.

Key job responsibilities
Own the design, implementation, and operation of core components of Prime Video's conversational discovery platform, delivering production-quality systems in a fast-moving, ambiguous environment

Design hybrid approaches that combine LLM-based semantic understanding with traditional personalization and ranking signals for content discovery and recommendation

Partner closely with applied scientists and fellow senior engineers to prototype, evaluate, and productionize LLM-powered features including personalized conversation starters, natural language query understanding, multi-turn dialogue, and contextual recommendations

Optimize LLM inference for latency, cost, and quality at the scale of one of the world's largest streaming services

Build evaluation and quality-gating mechanisms that measure relevance, personalization, diversity, and safety of LLM-generated content before and after launch

Contribute significant code, conduct thorough code reviews, and raise the engineering bar across the team

Uphold operational excellence for Tier-1 customer-facing AI systems, including on-call participation, root cause analysis, and driving reliability improvements

Collaborate across team and organizational boundaries to integrate with partner systems spanning inference infrastructure, feature storage, and experimentation platforms

Basic 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

Preferred qualifications

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 184,900.00 - 250,200.00 USD annually

How we rate this

Software Development Engineer III, Prime Video Personalization & Discovery at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Natural Language UnderstandingRecommendation SystemsDistributed SystemsInference OptimizationMachine LearningLLMs

Questions you could be asked

Tell me about a project where natural language understanding was part of your work. What did you do?
Tell me about a project where recommendation systems was part of your work. What did you do?
Tell me about a project where distributed systems was part of your work. What did you do?
Tell me about a project where inference optimization was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Natural Language Understanding, Recommendation Systems, Distributed Systems, Inference Optimization, and Machine Learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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