Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM

Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)? AWS Worldwide Specialists Org (WWSO) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. You will be part of the core worldwide GenAI Training and Inference team, responsible for defining, building, and deploying targeted strategies to accelerate customer adoption of our services and solutions across industry verticals.

About the role

You will be working directly with the most important customers (across segments) in the GenAI model training and inference space helping them adopt and scale large-scale workloads (e.g., foundation models) on AWS, model performance evaluations, develop demos and proof-of-concepts, developing GTM plans, external/internal evangelism, and developing demos and proof-of-concepts.

Responsibilities

• Help develop the industry’s best cloud-based solutions to grow the GenAI business.
• Work closely with engineering teams to enable new capabilities for customers to develop and deploy GenAI workloads on AWS.
• Facilitate the enablement of AWS technical community, solution architects, and sales with specific customer-centric value propositions and demos about end-to-end GenAI on AWS cloud.
• Drive engagement and interact at the highest levels with startups, enterprises, and AWS partners, leveraging a technical and business background.
• Articulate the potential and challenges of GenAI models and applications to engineering teams and C-level executives, requiring deep familiarity across the stack (compute infrastructure, ML frameworks, orchestration layers, parallel computing, MLOps, and target use cases in the cloud).
• Drive the development of the GTM plan for building and scaling GenAI on AWS.
• Interact with customers directly to understand their business problems and help define and implement scalable GenAI solutions (often via proof-of-concepts).
• Work closely with account teams, research scientists, and product teams to drive model implementations and new solutions.
• Help companies/partners understand best practices for operating on AWS.
• Partner with teams within AWS such as product teams, solutions architecture, sales, marketing, business development, and professional services.
• Represent your team to executive management.
• Learn, optimize, and build new technologies and techniques.
• Identify patterns and trends to broadly apply across industry segments or customer sets to accelerate innovation.
• Work with AWS ML and EC2 product teams to shape product vision and prioritize features for AI/ML frameworks and applications.

Requirements

• 7+ years of experience in specific technology domain areas (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
• 3+ years of experience in design, implementation, or consulting in applications and infrastructures.
• Experience developing, deploying, and managing AI products at scale.
• Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience working with PyTorch or JAX software.
• Bachelor’s degree in a technical discipline with 10+ years of technical design/implementation/consulting experience.
• Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking.
• Experience deploying and serving large language models for inference using container orchestration platforms like Kubernetes.
• Hands-on understanding of deep learning and other ML algorithms and infrastructure.
• Knowledge of MLOps tools and workflows for model development, validation, and deployment.
• Experience working with field teams to drive adoption of ML solutions.

Preferred Qualifications

• Master's degree or above in engineering or equivalent STEM (Science, Technology, Engineering, and Mathematics) field.
• Experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript.
• Experience communicating clearly and concisely with leadership, stakeholders, and cross-functional teams.
• Experience working with end user or developer communities.
• Experience working with 3rd party AI model providers to evaluate model quality/performance.
• Experience deploying models on model hosting platforms and/or working with early adopters of model APIs.
• Knowledge of vertical use cases for large language models in industries like finance, healthcare, retail, etc.
• Demonstrated ability to work effectively across internal and external organizations.
• Ability to influence product roadmaps based on customer needs and market traction.

About the team

The Frameworks team is highly specialized in computational workloads, performance evaluations, and optimization. We work with foundation model builders and large-scale training customers, diving deep into the ML stack including hardware (GPUs, Custom Silicon), operating system (kernel, communication libraries like NCCL and MPI), frameworks (PyTorch, NeMO, Jax), and models (Llama, Nemotron). We also work with containers (Docker, Enroot), orchestrators (EKS), and schedulers (Slurm).

Benefits

Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional 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 amazon.jobs/en/benefits.

Pay

• USA, CA, Mountain View: $176,600.00 - $239,000.00 USD annually
• USA, NY, New York: $169,000.00 - $228,600.00 USD annually
• USA, TX, Austin: $153,600.00 - $207,800.00 USD annually
• USA, WA, Seattle: $153,600.00 - $207,800.00 USD annually

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.