AmazonPosted 3d ago

Software Development Engineer, Alexa Excellence, Alexa LLM Inference, Capacity, & Efficiency

Software Development Engineer, Alexa Excellence, Alexa LLM Inference, Capacity, & Efficiency at Amazon scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

US, WA, Bellevuemidfull-time$165k-$224k

AI in this role

Design and maintain large-scale distributed systems and infrastructure services supporting LLM inference and GPU fleets.

bedrockllmgpudistributed-systems

software-engineeringmachine-learning-inferenceinfrastructurecapacity-planning

Are you passionate about building infrastructure that powers AI at scale? Do you want to work on systems that serve millions of Alexa customers every day? The Alexa AI Logistics for Infrastructure, Cost, and Efficiency (ALICE) team is looking for Software Development Engineers to join our Inferences Services Team.

We build products and solutions that enable Alexa service owners to analyze, forecast, and manage LLM infrastructure drivers, costs, and usage and inferences at large scale. You will be working on high-visibility, high-impact systems that are critical to the success of Alexa's next generation of AI experiences.

Key job responsibilities
- Design, develop, and maintain large-scale distributed systems and infrastructure services, leveraging GenAI at all phases of the development cycle
- Work on GPU fleet management and optimization for low-latency machine learning inference workloads at very large scale
- Collaborate with senior engineers/scientists to deliver features from design through production deployment
- Set standards and contribute to the operational excellence of Tier-1 production services
- Write clean, testable, maintainable code and participate actively in code reviews
- Work closely with partner teams across Alexa and AWS(Bedrock etc) to deliver cross-functional projects
- Research and identify opportunities to improve service performance, reliability, and cost efficiency

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
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience programming with at least one software programming language

Preferred qualifications

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Sunnyvale - 165,200.00 - 223,600.00 USD annually
USA, WA, Bellevue - 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 EngineeringMachine Learning InferenceInfrastructureCapacity PlanningBedrockLlmGpuDistributed Systems

Questions you could be asked

Tell me about a project where software engineering was part of your work. What did you do?
Tell me about a project where machine learning inference was part of your work. What did you do?
Tell me about a project where infrastructure was part of your work. What did you do?
Tell me about a project where capacity planning was part of your work. What did you do?
Walk me through how you've used Bedrock in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Software Engineering, Machine Learning Inference, Infrastructure, Capacity Planning, and Bedrock. 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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