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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM - **Company:** Amazon.com, Inc. - **Location:** San Diego, CA, United States - **Experience:** Experienced - **Salary:** $176,600.0 - $239,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Systems Engineering, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, TypeScript, Rust (Programming Language), Graphics Processing Unit (GPU), Pytorch, Large Language Models, Deep Learning, Parallel Computation, Generative AI, Kubernetes, Data Analytics, Slurm, Machine Learning Operations, Docker, Golang - **Published:** August 25, 2026 - **Apply:** https://www.amazon.jobs/en/jobs/10512074/worldwide-specialist-solutions-architect-genai-data-ai-gtm ## About the Role 7+ 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 - 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 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., 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. ## Description 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. 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. Key job 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. This is an opportunity to be at the forefront of technological transformations, as a key technical leader. Additionally, you will work with the AWS ML and EC2 product teams to shape product vision and prioritize features for AI/ML Frameworks and applications. A keen sense of ownership, drive, and being scrappy is a must. About the team The Frameworks team is highly specialized on computational workloads, performance evaluations and optimization. We work with Foundation model builders and large scale training customers, dive deep into the ML stack including the hardware (GPUs, Custom Silicon), operating system (kernel, communication libraries (NCCL, MPI), Frameworks (PyTorch, NeMO, Jax) and models (Llama, Nemotron...). We also work with containers (Docker, Enroot), orchestrators (EKS) and schedulers (Slurm). ## Related Videos - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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