Jobs · Consulting · Washington

GenAI/ML Specialist Solutions Architect, AGS Specialist Solutions Architects

Amazon Web Services (AWS) · Seattle, WA · 1 mo ago
ConsultingFull-time
We need to output HTML fragment with sections: h3 headings for sections present. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate (EEO, legal, etc). Must include sections only if real content. We need to parse description. Key parts: - Intro about AWS Global Sales, etc. That's prose. - Then "Are you passionate about AI..." etc. - Then description of Amazon's AI heritage. - Then description of AWS focus on AI stack. - Then "AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in the AMERICAS design solutions that leverage our ML services." - Then responsibilities bullet list: "As part of the team, you will work closely with ISV(Independent Software Vendors) to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward." - Then "You must have deep technical experience working with technologies related to Generative AI, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the GenAI space, and will leverage this knowledge to help AWS customers in their selection process." - Then location list: "If you are a qualified and accepted candidate, you may work out of any of the following cities: San Jose, Los Angeles, Denver, Chicago, Austin, Dallas, Atlanta, Arlington. Travel up to 50% across the USA may be possible." - Then "Key job responsibilities" heading (but we should not duplicate heading? The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to these standard headings. We have sections: About the role (intro), Responsibilities (key job responsibilities), Requirements (basic qualifications, preferred qualifications), Qualifications maybe same as Requirements? Skills maybe part of qualifications. Benefits: we have benefits description (health insurance etc). Pay: we have salary ranges per location. Schedule: maybe travel up to 50%? Could be schedule? Not exactly schedule but travel. Might be considered schedule? Probably not; schedule refers to work schedule (full-time, part-time). Not present. So we may omit Schedule. We must not create sections with filler like "commensurate with experience". We have actual salary ranges, so Pay section is valid. Benefits: we have description of benefits. Qualifications: we have basic and preferred qualifications. Skills: maybe we can include technical skills? Not explicit separate list; but we could embed within qualifications. Might not need separate Skills section. About the role: intro paragraphs. Responsibilities: the bullet list under "Key job responsibilities" plus maybe earlier responsibilities? We'll capture that. Requirements: maybe combine basic and preferred qualifications. We must not repeat job title as heading. We must not include Job ID etc. We must remove boilerplate: EEO, legal, accommodations, etc. Also remove "Los Angeles County applicants..." etc. Also remove "Our inclusive culture..." etc. Also remove "If you have a disability..." etc. Also remove "If the country/region you’re applying in isn’t listed..." etc. Also remove "Amazon is an equal opportunity employer..." etc. Also remove "Our inclusive culture empowers Amazonians..." etc. Also remove "Why AWS?" sections? Those are about AWS but maybe considered boilerplate? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. "Why AWS?" sections are promotional but not boilerplate? Might be considered part of description but could be kept? The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep substantive info about AWS culture etc? However those sections are generic marketing; but they are part of posting. The instruction says remove boilerplate like EEO etc. "Why AWS?" might be considered boilerplate but it's still part of the job description. However we need to decide. Usually these sections are considered generic but still part of posting. The instruction: "Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions." It does not say to remove marketing fluff like "Why AWS?" So we keep it. But we must ensure we don't include duplicated lines. We need to output only HTML fragment. Let's structure:

About the role

... intro paragraphs ...

Responsibilities

  • ...
  • ...

Requirements

Maybe split into Basic Qualifications and Preferred Qualifications as subheadings? But only allowed headings are those listed; we could still use

for subheadings? The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but to be safe we can use

for main sections and maybe

for subpoints. Could also use

but not specified. Safer to keep within allowed headings; we can put Basic Qualifications and Preferred Qualifications as

under Requirements? But that would duplicate heading level. Could instead have a single Requirements section with paragraphs listing basic and preferred. We'll include paragraphs.

Benefits

... benefits description ...

Pay

... salary ranges per location ...

We might also include

Skills

if we have explicit skills list; we don't. We must not include Schedule. Now we need to extract substantive content. Let's gather intro paragraphs: "AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and comprehensive support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/GenAI tools on Amazon Web Service (AWS)? Come join us! 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. Within AWS, we’re focused on bringing that knowledge and capability to customers through layers of the AI stack: 1) API-driven Inference Services like Amazon Bedrock 2) Agentic AI including Agentic platforms, tool usage, evaluations, governance and cost management along with use of Agentic SDKs such as Strands and platforms such as Amazon Bedrock AgentCore 3) Frameworks and Infrastructure with tools like Pytorch and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, k to quickly add intelligence to applications with simple API calls." Note there is a typo: "2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, k to quickly add intelligence to applications with simple API calls." Probably meant "and to quickly add intelligence". We'll keep as is. Now responsibilities: "As part of the team, you will work closely with ISV(Independent Software Vendors) to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward." Also earlier: "AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in the AMERICAS design solutions that leverage our ML services." That could be part of responsibilities or about the role. We'll include in About the role maybe. Now qualifications: Basic Qualifications: "2+ years of design, implementation, or consulting in applications and infrastructures experience 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience" Preferred Qualifications: "Experience working within software development or Internet-related industries Experience migrating or transforming legacy customer solutions to the cloud Experience working with AWS technologies from a dev/ops perspective" Also earlier: "You must have deep technical experience working with technologies related to Generative AI, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the GenAI space, and will leverage this knowledge to help AWS customers in their selection process." That could be part of qualifications/skills. We'll combine. Benefits: "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. Learn more about our benefits at https://amazon.jobs/en/benefits." Also earlier: "Your Amazon package will include sign-on payments and restricted stock units (RSUs)." That's compensation element but could be part of Pay? We'll include in Pay maybe. Pay: "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." Then list ranges: USA, CA, San Francisco - 151,000.00 - 204,300.00 USD annually USA, GA, Atlanta - 131,300.00 - 177,600.00 USD annually USA, MA, Boston - 131,300.00 - 177,600.00 USD annually USA, NY, New York - 144,500.00 - 195,400.00 USD annually USA, TX, Austin - 131,300.00 - 177,600.00 USD annually USA, WA, Seattle - 131,300.00 - 177,600.00 USD annually We'll include. Location: "If you are a qualified and accepted candidate, you may work out of any of the following cities: San Jose, Los Angeles, Denver, Chicago, Austin, Dallas, Atlanta, Arlington. Travel up to 50% across the USA may be possible." We could put location under About the role or maybe a separate

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