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

Location: United States; positions are based in Seattle, New York, or San Francisco. Travel of up to 30% may be required.

Salary: $153,600–$207,800 annually in Seattle; $169,000–$228,600 annually in New York; $176,600–$239,000 annually in San Francisco. Compensation may also include sign-on payments and restricted stock units.

Company

hirify.global Web Services is a comprehensive cloud platform providing infrastructure, data, machine learning, and generative AI services to organizations worldwide.

What you will do

• Design, prototype, implement, and deploy generative AI solutions for enterprise customers using AWS services.
• Build proofs of concept and guide customers through adoption patterns for hirify.global Bedrock and SageMaker.
• Develop reference architectures, white papers, blogs, presentations, and field enablement materials.
• Partner with data scientists, solution architects, sales, business development, and AWS service teams to accelerate customer adoption.
• Translate customer feedback into technical and business requirements for AWS product and engineering teams.
• Support a worldwide internal community of generative AI subject matter experts.

Requirements

• 4+ years of experience in application or infrastructure design, implementation, or consulting.
• Professional software development experience or strong foundations in machine learning and large language models, including architecture, training and inference lifecycles, and optimization.
• Master’s degree in a quantitative discipline such as data science, mathematics, engineering, or computer science.
• 4+ years working with data and AI technologies, including AI/ML, generative AI, analytics, databases, or storage.
• Deep experience with LLM architectures, model evaluation, fine-tuning, LLM agents, orchestration, embeddings, retrieval methods, security, and compliance.
• Experience with LangChain, LlamaIndex, data augmentation, responsible AI, performance evaluation frameworks, AWS services, and the AWS Well-Architected Framework.

Nice to have

• Experience training and deploying machine learning systems for large-scale optimization.
• Experience with distributed computing, Kubernetes, Docker, or container ecosystems.
• Experience working with developer communities and communicating with technical and executive stakeholders.
• Experience leading engineering discussions about product technology decisions and strategy.

Culture & Benefits

• Health, dental, vision, prescription, life, and AD&D insurance options.
• 401(k) matching, paid time off, parental leave, flexible spending accounts, and family-related reimbursement programs.
• Mentorship, knowledge-sharing, learning experiences, and career development resources.
• Work-life harmony, workplace flexibility, and employee-led inclusion groups.