AmazonPosted 2w ago

Software Development Engineer, Personalization, Amazon Personalization

Software Development Engineer, Personalization, Amazon Personalization at Amazon scores 90 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Seattleseniorfull-time$144k-$194k

AI in this role

Software Development Engineer needed to build large language model infrastructure and real-time personalization systems at scale.

large-language-modelspython

software-developmentai-infrastructuresystem-designpersonalization

What if Amazon knew not just what you like, but what your partner is into, what to get your mom for her birthday, and what toy your dog will actually play with? We're working on that.
You'll work at the intersection of large language models and real-time personalization, solving problems that are genuinely open and at a scale very few teams get to work on. We have the foundation shipped; now we need to go deeper.

Key job responsibilities
As a Software Development Engineer, you will build systems at the intersection of AI, real-time data, and customer personalization at Amazon scale.

1. Design and build services that use large language models to extract structured knowledge from natural language and serve it in real time across Amazon's biggest customer surfaces.
2. Build reliable infrastructure around AI systems that are inherently unpredictable, handling hallucinations, latency spikes, and model drift so customers always get a great experience.
3. Develop pipelines that process millions of customer signals daily into durable, retrievable, personalized data stores.
4. Create monitoring and evaluation frameworks for AI outputs where traditional testing doesn't apply, including automated quality measurement and human-in-the-loop validation.
5. Collaborate with Applied Scientists to take models from research to production, owning the path from prototype to scaled deployment.
6. Build customer-facing feedback loops where real-world corrections compound system quality over time.
7. Ship fast and incrementally, owning the full lifecycle from infrastructure to alarms to on-call.

About the team
We are Amazon's Customer360 Personalization team. We build the system that understands every important person in a customer's life and personalizes Amazon for each of them individually. We identify what customers care about from signals across all of Amazon and curate it into personalized experiences for every person in their life. Our engineers are hyper-productive, leveraging AI daily to accelerate their own work while building systems that overcome AI's limitations at scale. The team values builders who take full ownership of what they ship, move fast, ask for help early, and care more about customer outcomes than technical elegance.

Basic qualifications

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience designing or architecting (design patterns, reliability and scaling) of new and existing systems
- Experience with knowledge graphs, vector databases, or information retrieval systems

Preferred qualifications

- 3+ 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, WA, Seattle - 143,700.00 - 194,400.00 USD annually

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

Software DevelopmentAI InfrastructureSystem DesignPersonalizationLarge Language ModelsPython

Questions you could be asked

Tell me about a project where software development was part of your work. What did you do?
Tell me about a project where ai infrastructure was part of your work. What did you do?
Tell me about a project where system design was part of your work. What did you do?
Tell me about a project where personalization was part of your work. What did you do?
Walk me through how you've used Large Language Models in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Software Development, AI Infrastructure, System Design, Personalization, and Large Language Models. 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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