Senior Worldwide Specialist Solutions Architect - GenAI, Amazon Bedrock, Data & AI GTM

Amazon • Seattle, WA

1d • $153,600 - $239,000 • Remote

About The Position

This role is for a Senior Worldwide Specialist Solutions Architect focused on Generative AI (GenAI), Amazon Bedrock, and Data & AI Go to Market (GTM) strategies at AWS. The individual will help large customers build and deploy GenAI-enabled applications using Amazon Bedrock and SageMaker, fine-tune and build Generative AI models, and leverage these models for end applications. The role involves engaging with AWS product owners to influence product direction and helping enterprise customers tap into new markets using GenAI and AWS Services. Amazon has a long history of investing in AI and ML, with thousands of engineers dedicated to these fields. The AWS Generative AI Solutions Architect will act as a Subject Matter Expert (SME) for customers, understanding business problems, aiding in the implementation of GenAI solutions, delivering briefings and deep dives, and guiding customers on adoption patterns. This role is part of the Generative AI Worldwide Specialist organization, collaborating with other Solution Architects globally to enable large-scale customer use cases and drive adoption of AWS GenAI services. The individual will also provide guidance to other Data Scientists and Solution Architects in the field, develop thought leadership content (white papers, blogs, reference implementations, presentations), and create field enablement materials for broader technical teams. A key responsibility is driving feedback gathering from customers and translating it into requirements for product and engineering teams.

Requirements

• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 3+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
• 7+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 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.
• Proficient with prompt engineering, function calling, agentic workflows, embedding model fine tuning and retrieval method evaluation and optimization approaches.
• 5+ 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.
• Experience working with RESTful API and general service-oriented architecture.
• Deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques.
• Understand the security and compliance requirements for ML/GenAI implementations.
• Great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer.

Nice To Haves

• 5+ years of infrastructure architecture, database architecture and networking experience
• Experience with optimizing ML workloads using Model compression, distillation, pruning, sparsification, quantization, Transformers based algorithms like FlashAttention, PagedAttention, Speculative decoding, Distributed training/inference optimization, Hardware-informed efficient model architecture.
• Experience with distributed training and optimizing performance versus costs.
• Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex.
• Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM.
• Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches
• Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, & EMR.
• Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment.
• Track record of thought leadership and innovation around Machine Learning.
• Experience with Performance benchmarking and developing prescriptive guidance on optimally building, deploying and monitoring ML models on AWS to drive actions at scale to provide low prices and increased selection for customers.
• Experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, and Performance Evaluation frameworks.
• Experience architecting end to end ML/Gen AI applications for customers using AWS services and Well Architected Framework.

Responsibilities

• Implement, and deploy state of the art machine learning solutions under Gen AI.
• Build prototypes, PoCs, and explore new solutions.
• Interact closely with our customers.
• Advocate for AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
• Partner with Data Scientists, SAs, Sales, Business Development and the Generative AI Service teams to accelerate customer adoption and providing guidance on their customer engagements.
• Act as a technical liaison between customers and the AWS Generative AI services teams to provide customer driven product improvement feedback.
• Develop and support an AWS internal community of GenAI related subject matter experts worldwide.
• Create field enablement materials for the broader technical population, to help them understand how to integrate AWS GenAI solutions into customer architectures.

Benefits

• 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
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed