At a Glance
- Tasks: Design and implement cutting-edge AI/ML solutions for diverse business challenges.
- Company: Join the innovative AWS Professional Services team at Amazon.
- Benefits: Enjoy flexible work-life balance, mentorship, and career growth opportunities.
- Why this job: Be a key player in transforming businesses through cloud technology and AI.
- Qualifications: Experience in AWS services, cloud architecture, and strong programming skills required.
- Other info: Diverse experiences welcomed; apply even if you don't meet all qualifications.
The predicted salary is between 36000 - 60000 £ per year.
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to join our team at Amazon Web Services (AWS). In this role, you will work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You will be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle.
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You will work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
- Design and develop robust and scalable AI/ML solutions for business problems
- Interact with customers directly to understand the business problem, help and aid them in the implementation of their ML ecosystem
- Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs
- Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
- Comfortable working in a fast-paced, highly collaborative, dynamic work environment
- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
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 below, 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 - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences.
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 in the cloud.
BASIC QUALIFICATIONS
- Experience implementing AWS services in a variety of distributed computing environments
- 3+ years experience in cloud architecture, a ML practitioner with hands-on implementation of ML systems; building, validating and deploying GenAI models
- 5+ years of professional experience in a business environment; experience of IT platform implementation in a highly technical or analytical role
- 3+ years experience of handling large datasets and strong software development skills with proficiency in one or more programming languages including Python and one additional language e.g., Java, C#
- Strong understanding of DevOps practices with practical hands-on application and strong interest in AI/ML solutions. Strong verbal and written communications skills and ability to lead effectively across organizations in English
PREFERRED QUALIFICATIONS
- 3+ years Technical experience preferred, knowledge of AI/ML Technology stack of AWS and Generative AI trends, patterns, anti-patterns
- 3+ years Application Development experience required with serverless technologies and experience training distributed ML models on CPU and GPU hardware
- Serving ML models through real-time APIs and experience with deploying production-grade machine learning solutions on public cloud platforms. Knowledge of vertical use cases for large language models in industries like finance, healthcare, manufacturing etc
- AWS experience preferred, with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation). AWS Professional or Specialty level certifications (e.g., Machine Learning Specialty)
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences
Delivery Consultant - AI/ML, Professional Services, Professional Services in London employer: AWS EMEA SARL (UK Branch)
Contact Detail:
AWS EMEA SARL (UK Branch) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Delivery Consultant - AI/ML, Professional Services, Professional Services in London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that Delivery Consultant gig at AWS.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers and set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Research common questions for Delivery Consultant roles and practice your responses. Be ready to discuss your experience with AWS services and how you've tackled complex problems in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the AWS team and contributing to their mission.
We think you need these skills to ace Delivery Consultant - AI/ML, Professional Services, Professional Services in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Delivery Consultant role. Highlight your experience with AWS services and AI/ML solutions, as this will show us that you understand what we're looking for.
Showcase Your Skills: Don’t just list your skills; give us examples of how you've used them in real-world scenarios. Whether it’s designing scalable solutions or working with large datasets, we want to see your expertise in action!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon where possible. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you're serious about joining our team at AWS!
How to prepare for a job interview at AWS EMEA SARL (UK Branch)
✨Know Your AWS Inside Out
Make sure you have a solid understanding of AWS products and services, especially those related to AI/ML. Brush up on the latest features of Amazon Bedrock and SageMaker, as well as best practices for architecting scalable solutions. This knowledge will help you answer technical questions confidently.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed and implemented AI/ML solutions. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your ability to tackle complex business problems effectively.
✨Communicate Clearly and Effectively
Since you'll be interacting with customers and stakeholders, practice explaining technical concepts in simple terms. Use relatable analogies or examples to convey your ideas, ensuring that even non-experts can understand your approach and solutions.
✨Emphasise Collaboration and Mentorship
AWS values teamwork and knowledge sharing. Be prepared to discuss how you've collaborated with others in previous roles and any mentoring experiences you've had. Highlight your willingness to share knowledge and support your colleagues, as this aligns with AWS's inclusive culture.
