Senior GenAI Data Scientist - GenAI & AI Agents, AGS NAMER Specialist Team

Description

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud.

Join us and help us grow.

Are you a customer-obsessed builder passionate about helping enterprise customers achieve their full potential with Generative AI? Do you have deep data science expertise and the technical pre-sales acumen to help customers evaluate, design, and deploy GenAI and ML solutions on AWS? Do you enjoy building impactful AI agents and agentic applications? Join the GenAI/ML Specialist organization as a Senior Generative AI Data Scientist - a senior individual contributor role requiring deep data science expertise, hands-on ML engineering skills, and executive-level customer engagement.

The AGS Specialist organization is part of the customer-facing NAMER sales organization, and is responsible for driving revenue and accelerating adoption of cloud and partner services across diverse customer segments. We work backwards from our customers' most complex and business-critical challenges to develop and execute go-to-market plans that transform ideas into scalable, high-impact businesses. AGS NAMER teams include sales specialists and technical solution architects.

As part of the team, you will contribute across the full lifecycle of AWS customer initiatives-from shaping new service and solution concepts to accelerating adoption of established offerings. We pride ourselves on thinking big, delivering exceptional customer outcomes, and collaborating seamlessly across AWS as #One Team.

Role Description

In this role, you will be the Subject Matter Expert (SME) for helping NAMER Enterprise customers design and implement Generative AI solutions that leverage Amazon Bedrock. You will translate customer business challenges into data science-driven solutions using AWS. You will define, design, and deploy machine learning models, agentic workflows, and GenAI applications that accelerate adoption of AWS AI/ML services. You will engage with senior engineers, data scientists, product leaders, and executives at strategic enterprise customers to influence technical decisions and provide structured feedback to AWS product teams.

You will interact with customers directly to understand their business problems, help and aid them in implementation of generative AI solutions, deliver briefings and deep dive sessions, and guide customers on adoption patterns and best practices for generative AI. You will build prototypes, proof-of-concepts, and explore novel solutions leveraging Amazon Bedrock, Amazon Agent Core, Strands Agents, and open source frameworks such as Lang Chain, Lang Graph, and CrewAI.

This position will focus on agentic workflows with Amazon Bedrock, including Strands Agents, Bedrock Agents, and open source agentic frameworks. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents, tools, and orchestration approaches.

You will interface with customer data science teams, ML engineering leadership, and C-suite executives to advise on the latest techniques, model architectures, and emerging research. This includes staying current with state-of-the-art approaches from recent publications and research papers - such as advances in reasoning models, multi-agent systems, retrieval-augmented generation, reinforcement learning from human feedback (RLHF), and novel fine-tuning methods - and translating those findings into practical, production-ready solutions for enterprise customers.

You will lead technical deep dives and whiteboard sessions with customer chief data scientists and VPs of AI/ML, bridging the gap between research and real-world implementation on AWS.

You should understand the security and compliance requirements for ML/GenAI implementations. You should have experience architecting end-to-end ML/GenAI agentic applications for customers using AWS services and the Well-Architected Framework.

As the ideal candidate, you bring a deep data science background and the business…