Responsibilities

• You will help develop the industry’s best cloud-based solutions to grow the GenAI business.
• Working closely with our engineering teams, you will help enable new capabilities for our customers to develop and deploy GenAI workloads on AWS.
• You will facilitate the enablement of AWS technical community, solution architects and, sales with specific customer centric value proposition and demos about end-to-end GenAI on AWS cloud.
• You will possess a technical and business background that enables you to drive an engagement and interact at the highest levels with startups, Enterprises, and AWS partners.
• You will have the technical depth and business experience to easily articulate the potential and challenges of GenAI models and applications to engineering teams and C-Level executives.
• This requires deep familiarity across the stack – compute infrastructure (Amazon EC2, Lustre), ML frameworks PyTorch, JAX, orchestration layers Kubernetes and Slurm, parallel computing (NCCL, MPI), MLOPs, as well as target use cases in the cloud.
• You will 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 them with defining and implementing scalable GenAI solutions to solve them (often via proof-of-concepts).
• You will also work closely with account teams, research scientists, and product teams to drive model implementations and new solutions.
• You should be passionate about helping companies/partners understand best practices for operating on AWS. An ideal candidate will be adept at interacting, communicating and partnering with other teams within AWS such as product teams, solutions architecture, sales, marketing, business development, and professional services, as well as representing your team to executive management.
• You will have a natural appetite to learn, optimize and build new technologies and techniques. You will also look for patterns and trends that can be broadly applied across an industry segment or a set of customers that can help accelerate innovation.

Requirements

• 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• 3+ years of design, implementation, or consulting in applications and infrastructures experience
• 10+ years of IT development or implementation/consulting in the software or Internet industries experience
• 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
• 10+ years of technical specialist, design and architecture experience, or degree in advanced technology
• Experience in computer architecture, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
• 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.

Preferred

• Experience working with end user or developer communities
• 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 across at least one industry vertical (manufacturing, energy, oil & gas, etc.)
• Experience working with technical and product stakeholders to define requirements, prioritize features, and influence product roadmaps
• Experience working effectively across cross-functional teams and partnering well with people at all levels within an organization
• 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.

Benefits

• The base salary range for this position is listed below. 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. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for 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 https://amazon.jobs/en/benefits.