Key job responsibilities
- Design end-to-end AI/ML solutions by combining business understanding with deep technical expertise across the ML lifecycle, model training and fine-tuning, inference, and MLOps, ensuring architectures are extensible, secure, reliable, and cost-optimized while balancing short-term needs with long-term business outcomes. Guide customers on generative AI, foundation models, and classical ML, and help them select the right approach (e.g., prompt engineering, RAG, fine-tuning, or custom model training) for their use case.
- Serve as a trusted technical advisor to customer leadership, building relationships, understanding their data and technology challenges and industry context, and guiding their AI strategy through considered options and clear articulation of trade-offs, risks, and responsible-AI considerations such as governance, bias, security, and cost.
- Lead technical AI/ML solution discussions with customer teams, diving into model selection, data pipelines, training and inference architecture, evaluation, and best practices - proactively identifying high-risk or overly complex approaches (e.g., unnecessary model training, unscalable inference patterns) and engaging the right specialist and service-team resources when needed.
- Develop and deliver technical AI/ML content such as workshops, hands-on labs, presentations, blog posts, and reference architectures that educate customers on generative AI and ML strategy and best practices, applying your depth of experience to create reusable, high-quality artifacts that accelerate adoption.
- Collaborate with internal teams across sales, engineering, professional services, science, and product groups to accelerate AI/ML solution adoption, gather customer feedback on models and services, and translate it into clear requirements that improve the AI/ML product portfolio.
A day in the life
Your morning might start with a deep-dive architecture review alongside a customer's engineering team, working through design decisions for a cloud migration or a new application platform. After lunch, you could be whiteboarding a proof of concept that demonstrates how to simplify a complex workflow, then jumping into a call with product engineers to share feedback you've gathered from recent customer engagements. You'll regularly create and refine technical content, mentor fellow architects, and contribute to patterns that help the broader team deliver better solutions.
BASIC QUALIFICATIONS
- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 3+ years of design, implementation, or consulting in applications and infrastructures experience
- 8+ years of IT development or implementation/consulting in the software or Internet industries experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with at least one major cloud platform and its AI/ML services (e.g., SageMaker, Bedrock, or equivalents).
PREFERRED QUALIFICATIONS
- Experience architecting/operating solutions built on AWS
- 3+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 2+ years of practical machine learning experience
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, San Francisco - 176,600.00 - 239,000.00 USD annually
USA, CA, Santa Clara - 176,600.00 - 239,000.00 USD annually
