Software Development Engineer, Personalization, Amazon Personalization

AI in this role

Build foundational distributed systems and real-time retrieval architectures to give AI persistent memory.

pythondistributed-systemsapis

prompt-engineeringllm-integrationmachine-learningretrieval-augmented-generationknowledge-systemsbackend

What if AI didn't just execute — it got smarter every time it finished a task? We're building a new system that gives AI the ability to learn from experience at scale. Not through retraining, but through memory. You'll be among the first engineers building it — shipping production code in your first week on a team that moves at startup speed with Amazon resources.

Key job responsibilities
As a Software Development Engineer II, you will solve technical challenges at the intersection of knowledge systems, real-time retrieval, and AI-powered intelligence. You'll play an active role in translating research ideas into production systems and build quick prototypes in partnership with Applied Scientists and engineering leadership. Specific responsibilities include:

1. Design and build highly scalable distributed systems that capture, structure, and retrieve knowledge in real time across diverse data sources.
2. Implement intelligent retrieval and ranking capabilities that match intent to relevant knowledge with sub-second latency.
3. Create APIs and data models that enable AI systems to access structured memory across multiple contexts and domains.
4. Develop and optimize pipelines for processing both real-time event streams and batch data into durable, retrievable knowledge representations.
5. Build systems that respect temporal decay, relevance boundaries, and access controls to ensure knowledge stays current and appropriate.
6. Collaborate with Applied Scientists to integrate novel approaches to knowledge extraction and pattern recognition into production infrastructure.
7. Work on innovative solutions for cross-domain knowledge reconciliation — connecting insights that span different tools, teams, and workflows.
8. Contribute to the development of feedback loops that allow the system to compound its value with every interaction it processes.

About the team
We're a new team within Amazon's Personalization organization, which pioneered recommendation systems at internet scale. Our focus is different: not "what product should this customer see" but "what knowledge should this AI use right now." We're building a foundational capability that will change how hundreds of thousands of people work — giving AI persistent, compounding memory that improves with every interaction.

The team values builders who move fast, ship constantly, and are energized by solving problems that don't have established playbooks. We offer creative space with an entrepreneurial environment and a culture where everyone is a leader and owner for everything we do.

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 with knowledge graphs, vector databases, or information retrieval systems
- Familiarity with LLM integration patterns, prompt engineering, or agentic AI frameworks

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

How we rate this

Software Development Engineer, Personalization, Amazon Personalization at Amazon rates 90 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

Prompt EngineeringLLM IntegrationMachine LearningRetrieval Augmented GenerationKnowledge SystemsBackendPythonDistributed Systems

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How have you integrated a large language model into a production application?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where retrieval augmented generation was part of your work. What did you do?
Tell me about a project where knowledge systems was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, LLM Integration, Machine Learning, Retrieval Augmented Generation, and Knowledge Systems. 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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