A

Amazon

Sells products online and rents cloud computing

Solutions Architect 3 - Salesforce Account Team

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 5 years of experience in a specific technology domain such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data and analytics.
  • At least 3 years of experience in design, implementation, or consulting in applications and infrastructures.
  • At least 8 years of IT development or implementation/consulting experience in the software or Internet industries.
  • Experience with machine learning and large language model fundamentals, including architecture, training and inference lifecycles, and model execution optimization; alternatively, experience across the full software development lifecycle, 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, such as SageMaker, Bedrock, or equivalents.

Responsibilities

  • Design end-to-end AI/ML solutions across the machine learning lifecycle, including model training and fine-tuning, inference, and MLOps; ensure 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 machine learning, and help them choose approaches such as prompt engineering, retrieval-augmented generation, fine-tuning, or custom model training.
  • Advise customer leadership on AI strategy by understanding their data and technology challenges and industry context, explaining options and trade-offs, and addressing risks and responsible AI considerations including governance, bias, security, and cost.
  • Lead technical AI/ML solution discussions with customer teams, including model selection, data pipelines, training and inference architecture, evaluation, and best practices; identify high-risk or overly complex approaches and engage relevant specialists and service teams when needed.
  • Develop and deliver technical AI/ML materials, including workshops, hands-on labs, presentations, blog posts, and reference architectures, to educate customers on generative AI and machine learning strategy and best practices.
  • Collaborate with sales, engineering, professional services, science, and product teams to accelerate AI/ML solution adoption, gather customer feedback on models and services, and translate it into requirements to improve the AI/ML product portfolio.
  • Mentor fellow architects and contribute to reusable patterns that help the broader team deliver solutions.

Desired Qualifications

  • Experience architecting or operating solutions built on AWS.
  • At least 3 years of experience in a specific technology domain such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data and analytics.
  • At least 2 years of practical machine learning experience.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

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