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Key job responsibilities
You will help develop the industry’s best cloud-based solutions to grow the GenAI business. Working closely with our product and field teams, customers, and 3rd party model providers, you will help enable new capabilities for our customers to develop and deploy GenAI workloads on AWS. This involves activities like market sizing, building an opportunity pipeline, working with customers to understand technical requirements for proof-of-concepts (POC), creating content to train the field teams, and driving thought-leadership.You will possess a business and technical 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, ML frameworks, orchestration layers, large models, frameworks like LangChain for developing applications powered by GenAI models, 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.
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.AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
- 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
- Bachelor’s degree in technical discipline with 10+ years of technical design / implementation / consulting experience.
- Experience with building, validating and deploying GenAI models and applications.
- Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking.
- 5+ years of experience with large-scale distributed training and inference of foundation models using standard frameworks like PyTorch, TensorFlow, JAX etc.
- 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.
- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communities
- Master’s Degree or PhD in Engineering or related STEM field.
- 10+ years of engineering, technical business development, solutions architecture or equivalent field.
- 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.
- Experience with cloud computing and or related fields.
- Expertise with general purpose programming languages, including but not limited to: C/C++, C#, Python.
- Good business, and financial acumen.
- Demonstrated ability to work effectively across internal and external organizations is key.
- Ability to influence product roadmaps based on customer needs and market traction.
- Strong verbal and written communications skills and ability to lead effectively across organizations.
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