GenAI & ML Delivery Architect

Amazon Web Services (AWS); Arlington (VA); On-site; USD 131,000 - 178,000; Full time

Job summary

Amazon Web Services, Inc. is seeking a skilled ML Engineer to join AWS ProServe as a Delivery Consultant to design, implement, and manage AI/ML and GenAI solutions for enterprise customers.

You will work with customers to translate requirements into scalable architectures, drive deployment, and monitor outcomes across diverse industries. The role emphasizes mentorship, best practices, and cloud-first design.

Qualifications

• 3 years of software development experience.
• 3 years of building machine learning and generative AI models for business applications.
• Experience with cloud services related to ML (e.g., SageMaker) and generative AI applications.

Responsibilities

• Implement end-to-end AI/ML and GenAI projects from business needs to data prep, model development, deployment and monitoring.
• Design and implement ML pipelines that are high-performance, reliable, scalable, and secure.
• Design scalable ML solutions and MLOps using AWS services and leveraging GenAI where applicable.
• Collaborate with cross-functional teams to prepare, analyze, and operationalize data and ML models.
• Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures.
• Share knowledge and best practices through mentoring, training, and creating reusable artifacts.
• Ensure solutions meet industry standards and support AI/ML, GenAI, and cloud adoption strategies.

Skills

Software development

Machine learning

Cloud services

Tools

LangChain

LangGraph

LlamaIndex

PyTorch

TensorFlow

Job description

Amazon Web Services, Inc. is seeking a skilled ML Engineer to join AWS ProServe as a Delivery Consultant to design, implement, and manage AI/ML and GenAI solutions for enterprise customers.

You will work with customers to translate requirements into scalable architectures, drive deployment, and monitor outcomes across diverse industries. The role emphasizes mentorship, best practices, and cloud-first design.