Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM
About the role
Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)? The 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.
You will work 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. Your work will include model performance evaluations, developing demos and proof-of-concepts, creating GTM plans, external/internal evangelism, and collaborating with engineering teams to enable new capabilities for customers.
Responsibilities
- Develop industry-leading cloud-based solutions to grow the GenAI business, working closely with engineering teams to enable new capabilities for customers.
- Facilitate the enablement of the AWS technical community, solution architects, and sales teams with customer-centric value propositions and demos about end-to-end GenAI on AWS.
- Engage with startups, enterprises, and AWS partners at the highest levels, articulating the potential and challenges of GenAI models and applications to both engineering teams and C-level executives.
- Drive the development of GTM plans for building and scaling GenAI on AWS, interacting directly with customers to understand their business problems and help define scalable GenAI solutions (often via proof-of-concepts).
- Collaborate with account teams, research scientists, and product teams to drive model implementations and new solutions.
- Help companies and partners understand best practices for operating on AWS, identifying patterns and trends that can be broadly applied across industries or customer segments.
- Work with AWS ML and EC2 product teams to shape product vision and prioritize features for AI/ML frameworks and applications.
- Possess deep familiarity across the stack, including compute infrastructure (Amazon EC2, Lustre), ML frameworks (PyTorch, JAX), orchestration layers (Kubernetes, Slurm), parallel computing (NCCL, MPI), MLOps, and target use cases in the cloud.
Requirements
- 7+ years of experience in specific technology domain areas such as software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics.
- 3+ years of experience in design, implementation, or consulting for 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, or 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, and retail.
- 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 systems (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 options for supplemental life plans).
- Employee Assistance Program (EAP) and Mental Health Support.
- Medical Advice Line and Flexible Spending Accounts.
- Adoption and Surrogacy Reimbursement coverage.
- 401(k) matching.
- Paid time off and parental leave.
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.