Amazon Delivery Consultant – Application Developer 

United States, Texas, Arlington 

740201394

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.This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work.Key job responsibilities
As an experienced technology professional, you will be responsible for:
- Providing technical guidance and troubleshooting support throughout project delivery
- Collaborating with stakeholders to gather requirements and propose effective migration strategies- Sharing knowledge within the organization through mentoring, training, and creating reusable artifactsDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, 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.
Work/Life Balance
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.

- 5+ years of experience in cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 3+ years professional software development experience, including experience programming with at least one software language, and 3+ years of design or architecture (design patterns, reliability and scaling) of new and existing systems.
- 3+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models. Current, active US Government Security clearance.
- Clearance of TS/SCI with Polygraph

- AWS experience preferred, with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation)
- AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional) preferred
- Experience with automation and scripting (e.g., Terraform, Python)
- Knowledge of security and compliance standards (e.g., HIPAA, GDPR)
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field
- Experience using Python and frameworks such as PyTorch, TensorFlow, and practical experience in solving complex problems in an applied environment
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, as well as experience with machine learning, deep learning, NLP, generative AI, distributed training, and model hosting