GenAI/ML Solutions Architect — Delivery Lead

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

Benefits offered by this job

Health insurance

RSUs

Sign-on payments

Job summary

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

You will lead customer-focused project teams, provide technical leadership, and perform hands-on ML development with a focus on quality and cloud best practices, including secure architectures and scalable pipelines.

Qualifications

• 3+ years of cloud architecture and solution implementation experience.
• Knowledge of the primary AWS services (EC2, ELB, RDS, Route53 & S3).
• Experience implementing AWS services in a variety of distributed computing environments.

Responsibilities

• Lead project teams and implement end-to-end AI/ML and GenAI projects.
• Design and implement ML pipelines for high-performance, reliable, scalable ML workloads.
• Design scalable ML solutions and operations (MLOps) using AWS services and GenAI.
• Collaborate with cross-functional teams to prepare, analyze, and operationalize data and AI/ML models.
• Serve as a trusted advisor to customers 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 adoption strategies.

Skills

Cloud architecture

AWS services

ML/GenAI

Delivery leadership

Education

AWS Professional certification

Advanced technology degree

Tools

EC2

ELB

RDS

Route53

S3

Job description

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

You will lead customer-focused project teams, provide technical leadership, and perform hands-on ML development with a focus on quality and cloud best practices, including secure architectures and scalable pipelines.