Senior Solutions Architect - GenAI, AWS Cloud Intelligence

Amazon; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Mentorship & Career Growth

Work/Life Balance

Inclusive Team Culture

Flexible Working Hours

Job summary

An established industry player is seeking a Senior Solutions Architect specializing in Generative AI and Machine Learning. This role involves advising clients on cutting-edge AI technologies and designing innovative solutions using AWS services. The ideal candidate will possess deep technical expertise and a strong business acumen to communicate effectively with diverse stakeholders, from data scientists to C-level executives. Join a dynamic team that values mentorship, work-life balance, and an inclusive culture, where your contributions will drive significant advancements in AI solutions for customers worldwide.

Qualifications

• 8+ years of experience in customer-facing roles in AI/ML.
• Hands-on experience with deploying large language models.

Responsibilities

• Guide customers in selecting Generative AI and ML technologies.
• Collaborate with teams to deliver innovative AI solutions.

Skills

Generative AI

Machine Learning

Deep Learning

Customer Advisory

Problem Solving

Technical Consulting

Public Cloud Certifications

Education

Bachelor's Degree in Computer Science or related field

Tools

AWS AI/ML Services

Azure Machine Learning

SageMaker

Azure AI Services

OpenAI

Job description

Senior Solutions Architect - GenAI, AWS Cloud Intelligence

Job ID: 2897558 | Amazon Web Services, Inc.

Are you passionate about Generative AI (GenAI), Machine Learning (ML), and Deep Learning (DL)? Would you like to master these technologies across multiple providers to help customers build state-of-the-art solutions showcasing GenAI & ML’s potential?

As an Azure GenAI & ML Specialist in the AWS Cloud Intelligence team, you will be the Subject Matter Expert (SME) who advises customers on the differences between Azure’s and AWS’s AI, ML, and GenAI offerings. You will engage with product owners, marketing, and field leadership to position and differentiate AWS solutions in the AI/ML and GenAI space.

Ideal candidates have deep technical experience working with technologies related to artificial intelligence, machine learning, and/or deep learning. They must have the technical depth and the business acumen to communicate the benefits of AWS offerings to architects, data scientists, and C-level executives. They must be able to collaborate with cross-functional teams and think strategically to solve complex business and technical problems. They must have the inclination to share their insights and educate peers to foster a technical community of SMEs.

Key job responsibilities

1. Customer Advisor. Guide technical and business decision-makers through their Generative AI and Machine Learning technology selection process.
2. Thought Leader. Stay up to date with the ecosystem in the generative AI space. Analyze Azure, AWS, OpenAI, and Open LLMs to extract technical and business insights that drive technical and commercial differentiation, migration best practices, runbooks, and training content.
3. Field Leader. Deliver enablement activities and foster internal communities of Subject Matter Experts (SMEs) focused on generative AI. Collaborate across with marketing and Go-To-Market teams to deliver as #oneteam.
4. Solutions Architect. Work with customers’ development and data science teams to deeply understand their business and technical needs. Design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services to address their requirements.
5. Product Advisor. Act as technical liaison between customers and our service teams to influence customer-driving innovation and sustained leadership in the AI/ML space.

A day in the life

Why AWS? 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.

Mentorship & Career Growth: 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.

Work/Life Balance: 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.

Inclusive Team Culture: 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.

BASIC QUALIFICATIONS

1. Hands-on experience deploying, fine-tuning, and consuming proprietary and open large language models (LLMs) from top model providers like Amazon, Anthropic, OpenAI, Meta, Mistral, DeepSeek, etc.
2. 3+ years of experience in all phases of Machine Learning, Artificial Intelligence and Deep Learning solutions using Azure or AWS technologies.
3. 8+ years of customer-facing experience as a solutions architect, data scientist, technical consultant, or technical pre-sales.

PREFERRED QUALIFICATIONS

1. Experience with Azure Machine Learning, Azure AI Services, Azure OpenAI Service, Azure AI Foundry. Strong interest in maintaining this knowledge.
2. Experience with AWS technologies like SageMaker, Bedrock, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Polly, Amazon Personalize, and other AI/ML and GenAI services.
3. Track record of thought leadership and innovation around Machine Learning.
4. Experience as a leader and mentor, preferably in a data science team.
5. Sound business judgment with proven ability to influence business stakeholders.
6. Public cloud provider certifications: AWS, Azure, or Google Cloud.
7. Strong problem-solving skills. Demonstrated ability to analyze problems, develop actionable tactical plans quickly, and up-level the insights to strategy.
8. Demonstrated ability to be a "trusted advisor" to customers. Able to facilitate relationships with senior technical executives, as well as easily interact and give guidance to data scientists and system architects.
9. Excellent written and presentation communication skills.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.