Delivery Consultant — AI/ML & GenAI Solutions

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

Benefits offered by this job

health insurance

401(k) matching

paid time off

parential leave

Job summary

Amazon Web Services, Inc. is seeking an experienced ML Engineer to join the ProServe team as a Delivery Consultant. You will design, implement, and manage AWS AI/ML and GenAI solutions that meet customer objectives, guiding them through cloud adoption and best practices across the ML project lifecycle.

You’ll work with stakeholders to gather requirements, assess infrastructure, and propose migration strategies to AWS, while mentoring teams and ensuring secure, scalable deployments.

Qualifications

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

Responsibilities

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

Skills

Software development

ML model development

Cloud services experience

Tools

SageMaker

Bedrock

EC2

ECS

EKS

OpenSearch

AWS certifications

Job description

Amazon Web Services, Inc. is seeking an experienced ML Engineer to join the ProServe team as a Delivery Consultant. You will design, implement, and manage AWS AI/ML and GenAI solutions that meet customer objectives, guiding them through cloud adoption and best practices across the ML project lifecycle.

You’ll work with stakeholders to gather requirements, assess infrastructure, and propose migration strategies to AWS, while mentoring teams and ensuring secure, scalable deployments.