GenAI & ML Delivery Architect — AWS Pro Services

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

Job summary

AWS Professional Services is seeking a Delivery Consultant to design, implement, and manage AI/ML and GenAI solutions for enterprise customers. You will translate business needs into scalable AWS-based AI systems, drive cloud adoption, and ensure a secure, high-performance deployment.

In this customer-facing role, you’ll collaborate with cross-functional teams, mentor peers, and contribute best practices across the ML project lifecycle, with possible travel to customer sites as needed.

Qualifications

• 3+ years of customer-facing work solving business problems with advanced technologies
• 3+ years of building ML and GenAI models for business applications
• Experience with cloud ML services (e.g., SageMaker) and GenAI apps
• 3+ years coding, data querying (SQL) and scripting (Python)

Responsibilities

• Implement end-to-end AI/ML and GenAI projects from requirements to deployment and monitoring
• Design ML pipelines for high-performance, reliable, scalable, and secure workloads
• 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 trusted advisor to customers on AI/ML and cloud architectures
• Share knowledge through mentoring, training, publications, and reusable artifacts
• Ensure solutions meet industry standards and support adoption strategies

Skills

Customer-facing experience

ML/GenAI model development

SQL

Python

Tools

SageMaker

Bedrock

OpenSearch

LangChain

LangGraph

LlamaIndex

PyTorch

TensorFlow

Job description

AWS Professional Services is seeking a Delivery Consultant to design, implement, and manage AI/ML and GenAI solutions for enterprise customers. You will translate business needs into scalable AWS-based AI systems, drive cloud adoption, and ensure a secure, high-performance deployment.

In this customer-facing role, you’ll collaborate with cross-functional teams, mentor peers, and contribute best practices across the ML project lifecycle, with possible travel to customer sites as needed.