Delivery Consultant - AI/ML, Professional Services, Professional Services

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'll work closely with customers to design, implement, and manage AWS solutions that meet their technical requirements and business objectives. You'll 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'll 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 As an experienced technology professional, you will be responsible for:

1. Design and develop robust and scalable AI/ML solutions for business problems
2. Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
3. Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs
4. Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes

5. Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
6. Comfortable working in a fast paced, highly collaborative, dynamic work environment
7. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts, * 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., * 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 realtime 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

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 empower 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., 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. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.