AmazonPosted 3d ago

Software Development Engineer - Expert Consultant, AGI - Data Services

Software Development Engineer - Expert Consultant, AGI - Data Services at Amazon scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

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

AI in this role

Provide strategic engineering oversight for human-in-the-loop and model-in-the-loop data pipelines powering next-gen AI solutions.

pytorchtensorflowcudatritongpus

machine-learningdata-pipelinesmodel-traininggpu-optimizationllm

Amazon seeks a Software Engineering Domain Expert to provide strategic oversight of human-in-the-loop and model-in-the-loop data pipelines that power next-generation AI solutions. This role sits at the intersection of intellectual rigor and technological innovation — blending deep software development expertise with advanced analytical skills to ensure data excellence at every stage of the Model Training pipeline. The Domain Expert owns high-quality data output from end to end, translates training data needs into scalable engineering solutions, and fosters iterative development practices that raise the bar for the entire team. Beyond individual technical contribution, this role builds organizational capability through hands-on mentorship of junior engineers and strategic guidance on data quality standards. The right candidate thrives in ambiguity, brings clarity to difficult problems, and delivers measurable impact on the effectiveness and reliability of AI systems that serve millions of customers.

We are looking for candidates with expertise in accelerator architectures for ML or HPC such as GPUs, CPUs, FPGAs, or custom architectures, experience with GPU kernel optimization and GPGPU computing such as CUDA, NKI, Triton, OpenCL, SYCL, or ROCm, and knowledge of ML frameworks (PyTorch, TensorFlow) and their GPU backends.

Key job responsibilities
• Serve as a trusted domain advisor to cross-functional teams, providing strategic direction and specialized problem-solving support
• Champion domain knowledge sharing across multiple channels and teams to maintain data quality excellence and standardization
• Drive collaborative efforts with science teams to optimize output of complex data collections in your domain expertise, ensuring data excellence through iterative feedback loops
• Foster team excellence through mentorship and motivation of peers and junior team members
• Make informed decisions on behalf of our customers, ensuring that selected code meets industry standards, best practices, and specific client needs
• Collaborate with AI teams to innovate model-in-the-loop and human-in-the-loop approaches, to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more.
• Stay abreast of the latest developments in how LLMs and GenAI can be applied to your area of expertise to ensure our evaluations remain innovative
• Develop and write demonstrations to illustrate "what good data looks like" in terms of meeting benchmarks for quality and efficiency
• Provide detailed feedback and explanations for your evaluations, helping to refine and improve the LLM's understanding and output

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
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- 1+ years of Object Oriented Design 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
- 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, MA, Boston - 143,700.00 - 194,400.00 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

Machine LearningData PipelinesModel TrainingGpu OptimizationLlmPyTorchTensorFlowCuda

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?
Tell me about a project where model training was part of your work. What did you do?
Tell me about a project where gpu optimization was part of your work. What did you do?
Tell me about a project where llm was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine Learning, Data Pipelines, Model Training, Gpu Optimization, and Llm. 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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