AmazonPosted 7mo ago

Sr Software Development Engineer , AXU

Sr Software Development Engineer , AXU at Amazon scores 64 out of 100 on AI centrality, which makes it a Level 3 role on this board.

US, VA, Arlingtonseniorfull-time$168k-$227k

AI in this role

bedrock

prompt-engineeringragai-agentsai-automationai-evaluation

As a Software Development Engineer for Amazon eXperiences & Upskilling (AXU), you will be responsible for delivering the tools and processes required to ensure ensure every experience built with Amazon technologies naturally makes customers feel ‘this was designed for people like me.’ Our technology enables Amazon’s product, engineering, user experience, and science teams to understand how to build across Amazon broad range of customers, employees, and communities. We give teams scalable tools to deeply understand and connect with their customers, focusing on reaching and delighting a broader customer base.. You'll be at the forefront of building next-generation AI-powered solutions. This role is perfect for someone who combines deep technical expertise in large language models with hands-on experience architecting intelligent agent systems.
In this highly strategic, individual contributor role, you will work closely with cross-functional teams across Amazon to enable the delivery of transformative inclusive experiences. You will be relentlessly focused on providing Amazon's builders with the processes and tools that will make it effortless for teams to build truly inclusive products.
There will be ample opportunities to pitch ideas, design global systems and mentor junior engineers across the org. This is a rare opportunity to leave the world better than you found it by creating the tools that shape the future of inclusive experiences at Amazon. Apply now!

Key job responsibilities
As a Senior SDE on our team, you'll design and build sophisticated AI agent systems that leverage LLM & SLM technologies. You'll architect scalable solutions using Amazon Bedrock's agent core technologies, develop custom MCP servers, and create intelligent automation that transforms how our customers interact with AI. Your work will directly impact millions of users as you push the boundaries of what's possible with generative AI. In this highly strategic, individual contributor role, you will work closely with cross-functional teams across Amazon to enable the delivery of transformative experiences. You will be relentlessly focused on providing Amazon's builders with the processes and tools that will make it effortless for teams to meet even more customers, with everything they build.

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
- Experience managing and deploying ML products
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience as a mentor, tech lead or leading an engineering team
- Experience working with Learning Management Systems (LMS) to track and measure training results and learning effectiveness
- Advanced prompt engineering expertise (few-shot, chain-of-thought, ReAct, self-consistency techniques)
- Hands-on experience with MCP Tools and integrating agent frameworks
- Strong knowledge of Amazon Bedrock's agents, guardrails, knowledge bases, and model evaluation capabilities

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
- Experience developing cloud native CI/CD workflows and tools, such as Jenkins, Bamboo, TeamCity, Code Deploy (AWS) or GitLab
- Experience selling AI/ML solutions
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience with interrupt service routines
- Experience in A/B testing
- Experience with retrieval-augmented generation (RAG) using Amazon Bedrock Knowledge Bases and OpenSearch
- Familiarity with multi-agent orchestration, workflow automation using AWS Step Functions and Bedrock Agents

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, VA, Arlington - 168,100.00 - 227,400.00 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

Prompt EngineeringRagAI AgentsAI AutomationAI EvaluationBedrock

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a workflow you automated with AI tools, end to end.
How do you decide that one model's output is better than another's for a given task?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Automation, and AI Evaluation. 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.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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