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Lead Generative AI Solutions Architect, Amazon Bedrock GTM
2 months ago
Are you enthusiastic about Generative AI (GenAI)? Do you aspire to shape the future of Go to Market (GTM) strategies at Amazon Web Services (AWS) through generative AI? In this position, you will assist our prominent clients in constructing and deploying GenAI-enabled applications utilizing Amazon Bedrock and SageMaker. You will fine-tune and develop Generative AI models, enabling enterprise clients to harness these models for their applications.
Your Role: You will collaborate with AWS product teams to influence product development and assist clients in exploring new market opportunities by integrating GenAI with AWS Services.
About Us: At Amazon, we have been heavily investing in artificial intelligence for over two decades, and many features that customers enjoy in our products are powered by machine learning.
Our recommendations engine relies on machine learning (ML), as do the optimized robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also driven by ML algorithms.
Technologies like Alexa utilize Natural Language Understanding and Automated Speech Recognition deep learning, as do innovations like Prime Air and the computer vision technology in Amazon Go.
We have a vast team of engineers at Amazon dedicated to machine learning and deep learning, which is a significant part of our legacy.
Your Responsibilities: AWS is seeking a Generative AI Solutions Architect who will serve as the Subject Matter Expert (SME) in guiding clients to design solutions that leverage our Generative AI services.
You will engage directly with clients to comprehend their business challenges, assist them in implementing generative AI solutions, conduct briefing and deep dive sessions, and guide them on adoption strategies for generative AI.
As a member of the Generative AI Worldwide Specialist organization, you will collaborate with other Solution Architects across various regions to enable large-scale customer use cases and promote the adoption of Amazon Web Services for GenAI services.
You will also work alongside Data Scientists and Solution Architects in the field, providing guidance on their client engagements.
Key Contributions: You will create white papers, blogs, reference implementations, and presentations to empower clients and partners to fully utilize Generative AI services on Amazon Web Services.
Additionally, you will develop field enablement materials for the broader technical community to help them understand how to integrate AWS Generative AI solutions into client architectures.
You will facilitate effective feedback collection from clients, translating that feedback into clear business and technical requirements for product and engineering teams.
Qualifications: You must possess extensive technical experience with technologies related to large language models, including LLM architectures, model evaluation, and fine-tuning techniques.
Proficiency in designing, deploying, and evaluating LLM-powered agents and tools, as well as orchestration approaches, is essential. You should also be knowledgeable about embedding model fine-tuning and retrieval method evaluation techniques. Understanding security and compliance requirements for ML/GenAI implementations is crucial.
Experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, and Performance Evaluation frameworks is required. You should have a background in architecting end-to-end ML/GenAI applications for clients using AWS services and the Well-Architected Framework.
Essential Skills: Candidates must exhibit excellent communication skills and possess a strong technical background, capable of impressing Amazon Web Services clients at all levels, from executives to developers.
This role offers the opportunity to work directly with senior ML engineers and Data Scientists at clients, partners, and Amazon Web Services service teams, influencing their roadmaps and driving innovation.
Travel Requirements: Travel up to 50% may be necessary.
Key Job Responsibilities:
- Client Advisory: Implement and deploy cutting-edge machine learning solutions under GenAI. You will build prototypes, proof of concepts, and explore innovative solutions while closely interacting with our clients.
- Thought Leadership: Advocate for AWS GenAI services and share best practices through platforms such as AWS blogs, white papers, reference architectures, and public speaking events.
- Collaboration: Partner with Data Scientists, Solution Architects, Sales, Business Development, and Generative AI Service teams to accelerate client adoption and provide guidance on their engagements.
- Technical Liaison: Act as a technical bridge between clients and AWS Generative AI services teams to deliver customer-driven product improvement feedback.
- Community Development: Foster an internal AWS community of GenAI-related subject matter experts globally.
- Field Enablement: Create materials for the broader technical community to help them integrate AWS GenAI solutions into client architectures.
Basic Qualifications:
- 3+ years of experience in end-to-end technical architecture, design, deployment, and operations for Generative AI/ML platforms and applications.
- 1+ year of experience with technologies related to large language models, including LLM architectures, model evaluation, and fine-tuning techniques.
- Proficient in designing, deploying, and evaluating LLM-powered agents and tools.
- 5+ years of experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions using frameworks like TensorFlow and PyTorch.
- 5+ years of professional experience in software development using languages related to ML, such as Python or Java.
- 8+ years of experience in specific technology domains (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, engineering, or computer science.
Preferred Qualifications:
- Experience optimizing ML workloads using techniques like model compression, distillation, and pruning.
- Familiarity with distributed training and optimizing performance versus costs.
- Experience with open-source frameworks for building applications powered by language models.
- Customer-facing skills to effectively represent AWS within the client's environment.
- Experience with AWS technologies such as SageMaker, Step Functions, OpenSearch, and others.
- Demonstrated strategic thinking regarding business, product, and technical challenges in an enterprise context.
- Proven track record of thought leadership and innovation in Machine Learning.
- Experience with container platforms like Docker and Kubernetes.
- Experience with performance benchmarking and developing guidance on building, deploying, and monitoring ML models on AWS.
Diversity and Inclusion: Amazon is committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Compensation: Our compensation reflects the cost of labor across various US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on several factors, including market location and may vary depending on job-related knowledge, skills, and experience.
Benefits: Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be included as part of a total compensation package, alongside a comprehensive range of medical, financial, and other benefits.
