WW Specialist SA - GenAI, Amazon Bedrock Strategic Pursuit Team

AmazonSeattle, WA
274d$118,200 - $204,300

About The Position

Are you passionate about Generative AI (GenAI)? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help some of our largest customers build and deploy GenAI enabled applications using Amazon Bedrock and SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. At Amazon, we've been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com's recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it's a big part of our heritage. AWS is looking for a Generative AI Solutions Architect who will be the Subject Matter Expert (SME) for helping customers in designing solutions that leverage our Generative AI services. You will interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI. As part of the Generative AI Worldwide Specialist organization, you will work closely with other Solution Architects from various geographies to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI services. You will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. You must have experience with embedding model fine tuning and retrieval method evaluation approaches. You should understand the security and compliance requirements for ML/GenAI implementations. You must have experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, and Performance Evaluation frameworks. You should have experience architecting end to end ML/Gen AI applications for customers using AWS services and Well Architected Framework. Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation. Travel up to 30% may be possible.

Requirements

  • 2+ years of design, implementation, or consulting in applications and infrastructures experience.
  • 3+ years of specific technology domain areas experience (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
  • 1+ year experience working with technologies related to large language models including LLM architectures, model evaluation, adapters, model customization including pre-training and fine-tuning techniques.
  • Proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches.
  • 3+ years of experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions using one or more Deep Learning frameworks such as TensorFlow and PyTorch.
  • 5+ years professional experience in software development in languages related to ML like Python or Java.
  • Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, engineering, or computer science.

Nice To Haves

  • Experience with optimizing ML workloads using Model compression, distillation, pruning, sparsification, quantization.
  • Experience with distributed training and optimizing performance versus costs.
  • Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex.
  • Customer facing skills to represent AWS well within the customer's environment.
  • Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, & EMR.
  • Track record of thought leadership and innovation around Machine Learning.
  • Experience with Container Platforms (Docker, Kubernetes/Fargate).

Responsibilities

  • Help customers build and deploy GenAI enabled applications using Amazon Bedrock and SageMaker.
  • Engage with AWS product owners to influence product direction.
  • Deliver briefing and deep dive sessions to customers.
  • Guide customers on adoption patterns and paths for generative AI.
  • Develop white papers, blogs, reference implementations, and presentations.
  • Create field enablement materials for the broader technical field population.
  • Drive effective feedback gathering from customers and translate that feedback into clear business and technical requirements.

Benefits

  • Competitive salary based on market location and job-related knowledge, skills, and experience.
  • Equity, sign-on payments, and other forms of compensation may be provided.
  • Full range of medical, financial, and/or other benefits.

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Industry

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

Education Level

Master's degree

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