A

Amazon

Sells products online and rents cloud computing

Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 8 years of experience in specific technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data and analytics.
  • At least 3 years of experience designing, implementing, or consulting on applications and infrastructure.
  • At least 10 years of IT development or implementation/consulting experience in the software or Internet industries.
  • Experience developing, deploying, and managing AI products at scale.
  • Experience with machine-learning and large-language-model fundamentals, including architecture, training and inference lifecycles, and model-execution optimization, or experience working with PyTorch or JAX.
  • At least 10 years of technical specialist, design, and architecture experience, or a degree in advanced technology.
  • Experience in computer architecture, or experience developing and deploying large language models in production on GPUs, Neuron, TPU, or other AI-acceleration hardware.
  • Experience deploying and serving large language models for inference using container-orchestration platforms such as Kubernetes.
  • Hands-on understanding of deep learning and other machine-learning algorithms and infrastructure.
  • Knowledge of MLOps tools and workflows for model development, validation, and deployment.
  • Experience working with field teams to drive adoption of machine-learning solutions.

Responsibilities

  • Develop strategies to accelerate customer adoption of generative-AI model training and inference services and solutions across industry verticals.
  • Work directly with customers on large-scale generative-AI workloads, including foundation models; evaluate model performance; develop demonstrations and proofs of concept; and develop go-to-market plans and evangelism.
  • Work with engineering teams to enable customers to develop and deploy generative-AI workloads on AWS.
  • Enable the AWS technical community, solution architects, and sales teams with customer-focused value propositions and end-to-end generative-AI demonstrations on AWS.
  • Drive go-to-market planning for building and scaling generative AI on AWS.
  • Engage directly with customers to understand business problems and define and implement scalable generative-AI solutions, often through proofs of concept.
  • Work with account teams, research scientists, and product teams to drive model implementations and new solutions.
  • Identify patterns and trends that can be applied across industry segments or customer groups to accelerate innovation.
  • Work with AWS machine-learning and EC2 product teams to shape product vision and prioritize features for AI/ML frameworks and applications.
  • Lead end-to-end technical engagements with strategic customers by understanding their business context and designing AWS-powered solutions.
  • Present architectures to executive and technical stakeholders and guide implementation teams through adoption.
  • Represent the customer perspective to AWS service-team leaders, identify product gaps, and shape roadmap priorities.

Desired Qualifications

  • Experience working with end-user or developer communities.
  • Master's degree or above in engineering or an equivalent STEM field.
  • Experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript.
  • Experience communicating clearly and concisely with leadership, stakeholders, and cross-functional teams.
  • Experience in at least one industry vertical, such as manufacturing, energy, or oil and gas.
  • Experience working with technical and product stakeholders to define requirements, prioritize features, and influence product roadmaps.
  • Experience working effectively across cross-functional teams and partnering with people at all organizational levels.
  • Experience working with third-party AI model providers to evaluate model quality and performance.
  • Experience deploying models on model-hosting platforms or working with early adopters of model APIs.
  • Experience with physical AI workloads, including robotics simulation, autonomous systems, or real-time inference pipelines, and hands-on exposure to Isaac Sim, Isaac Lab, ROS/ROS2, or similar platforms.

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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