Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)? 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 key customers across segments in the GenAI model training and inference space, helping them adopt and scale large-scale workloads such as foundation models on AWS. Your responsibilities include developing GTM plans, external and internal evangelism, and creating demos and proof-of-concepts.

In this role, you will collaborate closely with customers to understand ML infrastructure requirements and the complexities involved in scaling GenAI model training across various modalities and use cases. You will leverage AWS's storage, compute, networking, and AI technologies to deliver scalable solutions. You will define GTM strategies, lead cross-functional initiatives to expand markets, develop scalable adoption programs, and identify new opportunities. Activities include market sizing, building opportunity pipelines, working with customers on technical requirements for proof-of-concepts, creating training content for field teams, driving industry thought leadership, collaborating with product teams on new features, and identifying partners and potential acquisitions.

The role requires a blend of business and technical expertise to lead engagements with startups and large enterprises. You will articulate the benefits of Open Source Frameworks and AWS services to data scientists, engineers, and executives. You will also engage with internal AWS teams (product, solutions architecture, sales, marketing, professional services) and external customers, partners, and the developer community. You will create compelling content and build scalable programs to increase awareness and adoption of ML Frameworks and AWS solutions. Additionally, you will work with AWS SageMaker and EC2 product teams to influence product vision and feature prioritization.

A keen sense of ownership, drive, and resourcefulness is essential. AWS values diverse experiences and encourages candidates from all backgrounds to apply. We foster an inclusive culture that supports learning, mentorship, career growth, and work-life balance.

Experience
- Bachelor's degree
- Experience developing, negotiating, and executing business agreements
- Experience in a professional field or military
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross-functional teams, building processes, and coordinating release schedules

About you
- Strong business and technology background enabling leadership of engagements with startups and large enterprises
- Domain expertise in key GenAI use cases, model learning techniques, large-scale distributed training and inference challenges
- Ability to orchestrate workloads using containers and GenAI infrastructure services
- Technical depth to articulate benefits of Open Source Frameworks and AWS services to diverse audiences including C-Level executives
- Passionate about GenAI market trends, ecosystem, and market development
- Excellent communication and collaboration skills to partner with internal teams and external customers, partners, and developer communities
- Ownership mindset, drive, and resourcefulness

Qualifications
- Preferred: MBA
- Preferred: Experience working with GenAI foundation models or startups in this space
- Preferred: Experience in pre-sales engineering, technical business development, strategic partnerships, or program/product management
- Preferred: Experience with cloud computing or related fields
- Preferred: Experience speaking at technology conferences and communicating across organizational levels
- Strong verbal and written communication skills with ability to lead effectively across organizations