Delivery Consultant AI/ML, Professional Services, AWSI HCLS

Delivery Consultant

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Delivery Consultant to serve as a technical builder for large-scale Healthcare and Life Sciences (HCLS) transformation programs. In this role as an individual contributor, you'll work closely with customers to design, implement, and manage AWS AI ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing hands-on technical builds and best practices throughout the project lifecycle.

You will bring a "T-shaped" profile: proficiency across AI/ML, architecture modernization, and data engineering, paired with distinctive depth in AI/ML. Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in building 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 builders to our customers, providing guidance on best practices, 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.

This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S. 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 include designing, implementing, and engineering complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs; providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services; collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies; and acting as a trusted builder to customers on emerging technologies.

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 empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

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.