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

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections with real content. We must not repeat job title as heading. No Job ID. Remove boilerplate. We need to extract substantive info. Let's parse description. First paragraph: "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." That's about the role. Then paragraph about Amazon heritage etc. Might be generic but still part of description. Then: "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." That's responsibilities. Then: "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." That's qualifications/requirements/skills. Then "Basic Qualifications" list. Then "Preferred Qualifications". Then benefits and pay info: "The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave." Then location salary ranges: "USA, CA, Irvine - 153,600.00 - 207,800.00 USD annually USA, CA, Palo Alto - 176,600.00 - 239,000.00 USD annually USA, MA, Boston - 153,600.00 - 207,800.00 USD annually" Thus we have Pay info. Schedule? Not mentioned. Travel up to 30% may be possible - that's not schedule but travel. No explicit schedule. Thus we can include sections: About the role, Responsibilities, Requirements (maybe combine Basic and Preferred?), Qualifications, Skills, Benefits, Pay. We need to decide which headings to use. The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can pick those that have content. We need to preserve all substantive info, not invent. We'll create sections:

About the role

with paragraph(s) summarizing role description.

Responsibilities

with bullet list of duties.

Basic Qualifications

maybe as Requirements? But they said Requirements heading. Could combine Basic and Preferred under Requirements? But they said we can have Requirements and Qualifications separate. Let's treat Requirements as Basic Qualifications, and Qualifications as Preferred Qualifications? Or Skills as technical skills. Better: Use Requirements for Basic Qualifications, Qualifications for Preferred Qualifications, Skills for technical proficiencies (LLM, LangChain, etc). Benefits for benefits, Pay for salary ranges. Let's extract bullet points. From responsibilities paragraph: list items: - Interact with customers directly to understand business problem - Help and aid them in implementation of generative AI solutions - Deliver briefing and deep dive sessions to customers - Guide customer on adoption patterns and paths for generative AI - Work closely with other Solution Architects from various geographies to enable large-scale customer use cases and drive adoption of AWS for GenAI services - Interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements - Develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on AWS - Create field enablement materials for broader technical field population to help them understand how to integrate AWS Generative AI solutions into customer architectures - Drive effective feedback gathering from customers, and distill and translate that feedback into clear business and technical requirements for product and engineering teams to review Also earlier: "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." That's also responsibility. Also "engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services." Also "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 (maybe under Responsibilities or separate). We'll include as bullet. Now Basic Qualifications list: - 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience - 3+ years of design, implementation, or consulting in applications and infrastructures experience - 10+ years of IT development or implementation/consulting in the software or Internet industries experience - 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience - Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience leading engineering teams as a mentor or tech lead - 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. - 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience. (duplicate) - Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, engineering, or computer science. We can deduplicate duplicates. Preferred Qualifications: - 5+ years of infrastructure architecture, database architecture and networking experience - Experience working with end user or developer communities - Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience making strategic business decisions and managing internal relationships, or experience troubleshooting problems and offering solutions to streamline complex challenges - Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience leading engineering teams as a mentor or tech lead Skills (technical proficiencies) maybe from earlier: deep technical experience with LLMs, LLM architectures, model evaluation, fine-tuning; proficient with design, deployment, evaluation of LLM-powered agents and tools and orchestration approaches; experience with embedding model fine tuning and retrieval method evaluation; understanding security and compliance; experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, Performance Evaluation frameworks; experience architecting end to end ML/Gen AI applications using AWS services and Well Architected Framework; great communication skills; ability to impress customers; etc. We'll put those under Skills. Benefits: health insurance list, 401(k) matching, paid time off, parental leave, sign-on payments, RSUs. Pay: salary ranges per location. We should not include boilerplate like EEO, LA County, accommodations, etc. Now produce HTML fragment. We'll wrap each section in

then content: for prose use

, for lists use

• . We need to avoid repeating job title. Let's craft. First About the role: combine introductory paragraphs. Paragraph: "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." Add also: "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." Might be part of About. We'll keep concise. Now Responsibilities
  . Now Requirements (Basic Qualifications)
  . Now Qualifications (Preferred)
  . Now Skills
  (technical proficiencies). Now Benefits
  . Now Pay
  maybe each location as li. We should not include Schedule. Now produce HTML. Check for any duplicated content: ensure we preserve all substantive info. Let's list all items to include. About the role: include the passion sentence, role description, helping customers, engaging with product owners, AWS looking for Generative AI Solutions Architect SME. Responsibilities: list as earlier. Requirements (Basic): list each bullet. Qualifications (Preferred): list each bullet. Skills: list technical proficiencies. Benefits: list. Pay: list salary ranges. Now produce.