Delivery Consultant - AI/ML, AWS Professional Services

Amazon Web Services (AWS) is a cloud platform provider whose Professional Services team helps customers achieve business outcomes through AWS Cloud adoption. The Delivery Consultant will design, implement, and manage AI/ML and Generative AI solutions, lead customers through ML project lifecycles, and provide technical guidance on cloud architectures, best practices, performance, and risk management.

Responsibilities

• Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring
• Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads
• Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable
• Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models
• Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
• Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts
• Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies

Skills

• Experience with AI/ML technologies
• 3+ years of building machine learning and generative AI models for business application experience
• 3+ years of customer-facing work, engaging with customer executives, technologists or partners to solve business problems with advanced technologies experience
• Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications
• 3+ years of coding, data querying languages (e.g. SQL), and scripting languages (e.g. Python)
• This is a customer-facing role with potential travel to customer sites as needed
• Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
• Knowledge of AWS services including SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch and AWS certifications
• 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools
• 3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow
• Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines
• Domain expertise in healthcare and life sciences

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance, including medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave
• Ongoing events and learning experiences
• Knowledge-sharing, mentorship and other career-advancing resources
• Flexibility as part of our working culture

Company Overview

• Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. It was founded in 2002, and is headquartered in Seattle, Washington, USA, with a workforce of 10001+ employees. Its website is http://aws.amazon.com.

Company H1B Sponsorship

• Amazon Web Services (AWS) has a track record of offering H1B sponsorships, with 7552 in 2026, 22803 in 2025, 21175 in 2024, 19057 in 2023, 24088 in 2022, 12233 in 2021, 14881 in 2020. Please note that this does not guarantee sponsorship for this specific role.