Delivery Consultant - AI​/ML, AWS Professional Services WWPS Life Science

Description

Final date to receive applications:
Jun 28, 2026.

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use?

Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades – pioneering and shaping the world’s AI technology?

The Amazon Web Services Professional Services (Pro Serve) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you’ll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You’ll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.

Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As a trusted advisor to our customers, you will provide guidance on industry trends, emerging technologies, and innovative solutions, leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.

• Implement end‑to‑end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
• Design and implement machine learning pipelines that support high‑performance, reliable, scalable, and secure ML workloads.
• Design scalable ML solutions and operations (MLOps) using AWS services and leverage GenAI solutions when applicable.
• Collaborate with cross‑functional teams (Applied Science, Dev Ops, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and ope rationalise data and AI/ML models.
• Serve as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures.
• Share knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
• Ensure solutions meet industry standards and support customers in advancing their AI/ML, GenAI, and cloud adoption strategies.

This is a customer‑facing role with potential travel to customer sites as needed.

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

• 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 Sage Maker) and generative AI applications.
• 3+ years of coding, data querying languages (e.g., SQL), and scripting languages (e.g., Python).

• Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies.
• Knowledge of AWS services including Sage Maker, Bedrock, EC2, ECS, EKS, Open Search and AWS certifications.
• 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like Lang Chain, Lang Graph, Llama Index, and/or similar tools.
• 3+ years of deep learning,…