Sr Delivery Consultant
23 hours ago
Possessing a deep understanding of AWS products and services, as a Sr. 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. Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimization
2. Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on using Amazon Bedrock, SageMaker etc.
3. Provide technical leadership and mentorship to other consultants while driving best practices across delivery teams
4. Partner with customers to translate business challenges into measurable outcomes and clear delivery roadmaps
5. Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
6. Influence customer AI strategy through technical expertise and industry insights
7. Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions
8. Provide thought leadership in internal and external engagements
9. Support pre-sales activities to provide technical expertise and review project scoping and risks
A day in the life
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 (gender 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.
- Strong experience in building large scale machine learning or deep learning models and in Generative AI model development. Experience in data and machine learning engineering and cloud native technologies. Strong experience communicating across technical and non-technical audiences
- Strong experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation
- Master's degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science
- Knowledge of data modelling principles, statistical analysis methodologies, and demonstrated ability to extract meaningful insights from complex, large-scale datasets.
- AWS Associate level certifications (e.g., Machine Learning Specialty, Machine Learning Engineer Associate, Solutions Architect Professional) preferred. Experience with software development life cycle (SDLC) and agile/iterative methodologies
- Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet
- Knowledge of the primary AWS services (EC2, RDS, Route53 & S3).Experience with automation and scripting (e.g., Terraform, Python). Knowledge of security and compliance standards (e.g., HIPAA, GDPR)
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 ) to know more about how we collect, use and transfer the personal data of our candidates.
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 for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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