AmazonSr. Software Development Engineer, Guidance & Personalization
Amazon is hiring a Sr. Software Development Engineer, Guidance & Personalization in New York, United States. It pays $185k-$250k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- Pay on this posting starts 11% higher than the typical software engineer posting on Level.
- The posting mentions Distributed Systems, ML Infrastructure and AI agents among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Build AI-native, explainable personalization and multi-agent systems for large-scale advertising recommendation engines.
We're looking for a Sr. Software Development Engineer to join the Personalization & Guidance team — a high-growth team building AI-native systems that make advertising more intelligent, transparent, and effective for the advertisers who rely on them every day.
Advertising personalization is a well-studied domain. What makes this team's work different is the explainability constraint — we're building systems where the why behind a recommendation is a first-class product concern, not an afterthought. That drives real architectural decisions: how you store and version the inputs to a decision, how you surface confidence, how you maintain auditability across distributed agent systems, and how you enforce content quality standards at render time rather than at authoring time.
Key job responsibilities
You'll work on systems that sit at the core of how advertisers understand and act on their advertising performance. The problems are technically hard:
- Personalization at scale — building and maintaining structured models of advertiser behavior, goals, and preferences that update continuously across millions of accounts and inform real-time decisions
- Real-time ML inference — systems that evaluate and rank recommendations, guidance, and actions at high volume with tight latency constraints across distributed infrastructure
- Explainable AI systems — infrastructure that makes automated decisions auditable and legible to end users, not just to engineers. This includes stable data models for tracking decision inputs, surfacing confidence signals, and rendering explanations that advertisers can inspect and act on
- Multi-agent coordination — APIs and contracts that allow multiple specialized AI agents to contribute outputs into a unified experience, with quality enforcement at the delivery layer
- Event-driven data pipelines — high-volume ingestion, processing, and serving of advertising signals that feed both the ML models and the real-time recommendation systems
A day in the life
You'll work in a space where ML infrastructure, distributed systems, and product-quality UX concerns intersect daily.
Technology You'll Work With:
- Large-scale distributed systems built on cloud infrastructure (microservices, event streaming, real-time serving)
- Machine learning infrastructure — model serving, feature stores, A/B testing frameworks, online evaluation
- Large language models and agentic AI systems — integrating LLM-powered agents into production advertising workflows, with the reliability and observability requirements that entails
- High-volume data pipelines processing advertising signals across formats and surfaces
- API design for multi-team and multi-agent consumption patterns
About the team
What We're Looking For:
- Strong distributed systems fundamentals — you've built services that have to be both fast and correct under real traffic
- Experience with ML infrastructure or production ML-adjacent systems; you understand what it takes to build reliable systems around probabilistic models
- Product instincts — you care that the output is useful and legible to the person using it, not just that the pipeline ran successfully
- Comfort with ambiguity — the team is working in a fast-moving space where some of the right architectural decisions are still being established
- Strong written communication — our most consequential technical decisions live in design documents, and engineers are expected to author them
If you want to work on systems that are technically sophisticated, have real daily impact on advertisers around the world, and are building into a space — AI-driven advertising — that is genuinely changing how the industry works, this team is worth a conversation.
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
Sr. Software Development Engineer, Guidance & 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.
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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $185k
- Typical software engineer job
- $167k
This posting starts 11% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where software development was part of your work. What did you do?
- Tell me about a project where real time inference was part of your work. What did you do?
- Tell me about a project where explainable ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI agents, Machine learning, Software Development, Real Time Inference, and Explainable AI. 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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