TavilyRemote · London, United Kingdom; Remote - Europe
AmazonPosted 5mo ago
Senior AI Sales Specialist at Amazon scores 69 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
This role partners closely with customers to understand their goals, translate complex AI capabilities into clear business value, and support successful AI adoption at scale. If you enjoy collaborating with diverse stakeholders, communicating technical concepts with clarity, and contributing to long-term customer success, we encourage you to apply.
AWS Global Sales supports customers of all sizes across the region to innovate and grow in the cloud. As organizations increasingly adopt foundation models, large language models (LLMs), and agentic AI, we are expanding our team of sales professionals. We are seeking professionals who can help customers identify and prioritize AI use cases to create AWS opportunities, build sustainable pipelines, and guide customers through complex AI adoption journeys.
Key job responsibilities
Sales & Revenue Contribution:
o Support the achievement of sales targets by developing and maintaining a healthy pipeline and guiding customers through end-to-end sales cycles, from discovery through to agreement;
o Create detailed account plans and territory strategies in partnership with internal teams, while maintaining accurate forecasting using CRM tools;
o Collaborate with customers to identify and qualify high-impact AI use cases aligned to their business priorities and strategic objectives.
• Sales & Solution Advisory
o Act as a trusted advisor on AWS AI services, helping customers understand potential outcomes, value, and return on investment;
o Lead technical discovery sessions and contribute to demonstrations, proofs of concept, and solution design, including model selection, fine-tuning, and deployment approaches;
o Provide guidance on model evaluation, responsible AI practices, governance considerations, and relevant compliance requirements.
• Customer Engagement & Market Development
o Build and maintain strong relationships with decision-makers and executive stakeholders through a consultative, collaborative approach;
o Partner with internal teams to deliver workshops, enablement sessions, and solution reviews that support customer learning and adoption;
o Share customer insights and feedback with AWS AI product teams to help inform product direction and improvements.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
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.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Basic qualifications
- 7+ years of technology role experience
- Experience in setting up and managing a sales pipeline
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
Preferred qualifications
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Experience developing, deploying and managing AI products at scale
- Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
- Bachelor's degree in computer science, machine learning, engineering, or related fields, or Master's degree
Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: Fine Tuning, AI Evaluation, Nlp, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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