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

Amazon.com Inc
  • Seattle, WA
    2 days ago

    Job Description

    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.

    Key job responsibilities

    • Customer Advisor- Implement, and deploy state of the art machine learning solutions under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers.
    • Thought Leadership - 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.

    About the team

    Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

    We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

    We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

    Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

    AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

    Numbers & Facts

    LocationSeattle, WA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles
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    Skills

    • Algorithmsunmatched
    • Amazon Alexaunmatched
    • Amazon Web Services (AWS)unmatched
    • Architectural Analysisunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Blogunmatched
    • Business Developmentunmatched
    • Capacity Managementunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Computer Visionunmatched
    • Conferencesunmatched
    • Customer Acquisitionunmatched
    • Customer Experienceunmatched
    • Customer Relationsunmatched
    • Customer Support/Serviceunmatched
    • Customer/Client Researchunmatched
    • Data Scienceunmatched
    • Deep Learningunmatched
    • Diversityunmatched
    • Forecastingunmatched
    • Leading Edge Technologyunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Modeling Languagesunmatched
    • Online Customer Supportunmatched
    • Order/Customer Fulfillmentunmatched
    • People Managementunmatched
    • Performance Analysisunmatched
    • Performance Reviewsunmatched
    • Presentation/Verbal Skillsunmatched
    • Process Improvementunmatched
    • Product Engineeringunmatched
    • Prototypingunmatched
    • Regulatory Complianceunmatched
    • Retailunmatched
    • Salesunmatched
    • Speech Recognitionunmatched
    • Startupunmatched
    • Supply Chainunmatched
    • Thought Leadershipunmatched
    • Use Casesunmatched
    • White Papersunmatched
    • Willing to Travelunmatched

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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