At a Glance
- Tasks: Drive AWS GenAI/ML adoption and design innovative solutions for enterprise customers.
- Company: Join Amazon, a leader in cloud technology and innovation.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Work with top-tier clients and build lasting relationships in a dynamic environment.
- Why this job: Be at the forefront of AI technology and make a real impact on businesses.
- Qualifications: Deep expertise in Generative AI, Machine Learning, and customer-facing technical roles.
The predicted salary is between 72000 - 88000 £ per year.
AWS is seeking a Senior GenAI/ML Specialist Solutions Architect (SSA) for large enterprise customers in the United Kingdom of Great Britain and Ireland (UKI). You'll be instrumental in driving the adoption of AWS GenAI/ML services while helping organizations achieve their innovation and transformation goals through GenAI/ML architectures. This role requires technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AGS organization, SSAs work with customers who have complex requirements that require expert-level knowledge to solve.
You must have deep technical expertise in Generative AI and Machine Learning services, enterprise-grade architectural strategies, and a passion for solving complex business challenges. We are looking for technical experts who can bridge the gap between innovative AI technologies and practical business outcomes for our customers. You'll work directly with a diverse top range of customers in UKI to help them make optimal technical decisions in their AI/ML journey, balancing innovation with practical constraints and compliance requirements. You'll have the opportunity to build enduring relationships with these organizations and establish yourself as a trusted technical advisor in the rapidly evolving field of Generative AI and Machine Learning.
Key job responsibilities
- Technical Expertise & Solution Design: Provide customers with deep technical expertise in Generative AI and Machine Learning technologies, designing innovative solutions that help them meet strategic business objectives using AWS products.
- Customer Advisory: Act as a trusted advisor to line of business, AI, Data, and C-suite leaders, translating complex technical concepts into business value and guiding their AI transformation journey.
- Technical Leadership: Lead architectural reviews, workshops, and proof-of-concepts to advance customers' technical objectives and validate proposed solutions.
- Thought Leadership: Share best practices through AWS blogs, whitepapers, reference architectures, and helping to educate the broader technical community.
- Product Feedback & Innovation: Gather customer insights to inform AWS product teams about market needs and opportunities, contributing to the evolution of AWS GenAI/ML services based on real-world implementation experience.
- External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS Summit and re:Invent.
A day in the life: You bring hands-on experience designing and implementing machine learning solutions, including model training, deployment, and inference at scale, with working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn. You have a background in a customer-facing technical role (solutions architect, ML engineer, data scientist, or technical consultant) and can communicate complex technical concepts to both technical and non-technical audiences, including C-suite executives. You hold domain expertise in one or more of: natural language processing, computer vision, generative AI, recommendation systems, or conversational AI.
Ideally, you also have experience with large language models (LLMs), foundation models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon Q, or Amazon Rekognition is highly valued. Experience architecting end-to-end ML pipelines including data ingestion, feature engineering, model training, evaluation, and production deployment (MLOps) would further strengthen your candidacy.
Qualifications
- Bachelor's degree in computer science, engineering, mathematics or equivalent, or experience in a professional field or military.
- Experience in IT development or implementation/consulting in the software or Internet industries.
- Experience within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
- Experience in design, implementation, or consulting in applications and infrastructures.
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients.
- Knowledge of SAP systems (like SAP Business Suite, S/4HANA, SAP Business Warehouse, SAP HANA, SAP Business Objects, etc.) and their architecture and infrastructure needs.
- Experience in infrastructure architecture, database architecture and networking.
- Experience working with end user or developer communities.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.
Senior GenAI/ML Specialist SA, UKI-AWS Global Sales (AGS) in London employer: AWS.
As a Chief Engineer in Data Centre Engineering Operations, you will be part of a dynamic team dedicated to maintaining AWS's global infrastructure, ensuring that our cloud services run seamlessly. We pride ourselves on fostering a collaborative work culture that encourages innovation and professional growth, offering extensive training and development opportunities. Located in a vibrant tech hub, our employees enjoy a stimulating environment with access to cutting-edge technology and the chance to make a significant impact in the cloud computing industry.
StudySmarter Expert Advice🤫
We think this is how you could land Senior GenAI/ML Specialist SA, UKI-AWS Global Sales (AGS) in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at AWS. or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to AWS..
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like AWS..
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like AWS. that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior GenAI/ML Specialist SA, UKI-AWS Global Sales (AGS) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at AWS..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at AWS. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at AWS.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If AWS. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
