A

Amazon

Sells products online and rents cloud computing

Senior AI Solution Architect

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • At least 7 years of design, implementation, or consulting experience with distributed applications.
  • At least 5 years of customer-facing experience designing or implementing production AI systems.
  • Experience implementing AI solutions, which may include integrating large language models or multimodal foundation models into large-scale systems, fine-tuning large language models, deploying and performing distributed inference of large language models, retrieval-augmented generation, foundation model evaluation, vector databases, agentic workflows, prompt and context engineering, and machine learning operations.
  • Hands-on experience with AWS ecosystems, including Bedrock, AgentCore, and SageMaker, or equivalent, to establish secure private-network AI environments.
  • Practical experience implementing retrieval-augmented generation using embeddings, vector stores, and semantic search optimization.
  • Ability to communicate effectively with diverse internal and external audiences.
  • Ability to influence customer and internal business decision-makers as a technical thought leader.

Responsibilities

  • Build technical relationships with customers of all sizes and serve as a trusted advisor, helping them use cloud services throughout their journey while adopting generative AI, machine learning, and agentic technologies.
  • Manage the overall technical relationship between AWS and customers, recommending approaches for security, cost, performance, reliability, and operational efficiency to advance their generative AI, machine learning, and agentic projects.
  • Represent customer needs internally regarding their use of services and inform the roadmap for AWS generative AI, machine learning, and agentic features.
  • Define cloud-native generative AI, machine learning, and agentic architectural patterns for a range of use cases.
  • Create and share best practices, technical content, and reference architectures, including white papers, code samples, and blog posts.
  • Educate and promote the use of AWS technology for generative AI, machine learning, and agentic workloads through workshops, user groups, meetups, public speaking, online videos, or conferences.
  • Lead hands-on technical deep dives and workshops, and contribute reusable code, reference architectures, and internal technical assets for the broader engineering organization.

Desired Qualifications

  • Technical cloud certification.
  • Ability to lead projects with complex challenges and deliver extensible, operationally excellent, cost-optimized solutions aligned with desired outcomes.
  • Ability to lead a team or small organization-wide initiative with partially defined business objectives.
  • Ability to determine solution strategy and where to simplify or extend solutions for the best outcome.
  • Master's degree in Computer Science, Mathematics, or Statistics, or a PhD; an equivalent quantitative field is also acceptable.
  • Experience running and fine-tuning large and small language models using techniques such as LoRA/QLoRA, instruction tuning, and reinforcement learning from human feedback to optimize for specific domain tasks.
  • Expertise architecting AI systems in highly regulated or security-sensitive environments, such as financial services, healthcare, or the public sector.

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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