Delivery Consultant - AI/ML, Professional Services

Amazon is hiring a Delivery Consultant - AI/ML, Professional Services in Milan, Italy. It pays €56k a year and Level rates it ; you can apply on Level.

AI in this role

langchainlanggraphbedrocksagemaker

ragfine-tuningml-opsai-evaluationcomputer-visionai-safety

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Data and GenAI Architect to join our team at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS data-driven and AI 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 project lifecycle, with a specific focus on data architecture, AI/ML implementations, and generative AI solutions.

Possessing a deep understanding of AWS products and services, as a Data and GenAI Architect you will be proficient in architecting complex, scalable, and secure data platforms and AI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current data infrastructure, and propose effective strategies for implementing modern data architectures and GenAI solutions on AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging AI technologies, and innovative data solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption, with particular emphasis on data modernization and AI transformation. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.

Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Designing and implementing complex, scalable, and secure AWS solutions tailored to customer needs
2. Providing technical guidance and troubleshooting support throughout project delivery
3. Collaborating with stakeholders to gather requirements and propose effective migration strategies
4. Acting as a trusted advisor to customers on industry trends and emerging technologies
5. Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts

About the team
AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Basic qualifications

- 3+ years of experience designing and delivering cloud-based data and AI/ML solutions
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience
- Experience in software development with an object-oriented programming language (e.g., Python, Java)
- Hands-on experience deploying and hosting generative AI or machine learning solutions in production, including model training or fine-tuning and inference
- Working knowledge of machine learning, deep learning, and statistics
- Experience designing generative AI solutions, including Retrieval-Augmented Generation (RAG), vector databases, and agent-based architectures
- Experience with LLM evaluation, guardrails, and MLOps/LLMOps, including monitoring, cost and performance optimization of inference, and AI security, privacy, and responsible AI practices
- Experience in a customer-facing role, with excellent written and verbal communication skills and the ability to present technical solutions to technical and executive audiences

Preferred qualifications

- Master's degree or PhD in Computer Science, Engineering, Mathematics, Statistics, or a related technical or scientific field
- 5+ years of experience delivering data and AI/ML solutions at scale in enterprise or consulting environments
- Hands-on experience with deep learning architectures (e.g., Transformers, diffusion models, CNNs), computer vision, or distributed training
- Experience with agentic frameworks (e.g., Strands Agents, LangChain, LangGraph) and the Model Context Protocol (MCP)
- Experience with AWS services such as Amazon SageMaker AI, Amazon Bedrock, Amazon EMR, Amazon S3, Amazon OpenSearch Service, AWS Step Functions, AWS Lambda, and Amazon EC2

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The minimum gross base salary for this position is listed below. The base salary listed corresponds to working on a full-time basis. For part-time hours, the salary will be pro-rated.

Amazon reserves the right to offer a higher salary and/or level, depending on the candidate's skills, competencies, and experience. Amazon's package may include a sign on payment. In addition, the candidate may be eligible to participate in a restricted stock unit scheme operated independently by Amazon.com Inc. in USA. Your recruiting team will share final salary and any restricted stock unit scheme if applicable, depending on skills and requirements.

In addition to statutory benefits, and those applicable to the relevant CBA, company supplementary benefits may apply subject to further terms.

See below the minimum gross base salary for this position:

Milan, ITA - 55,500.00 EUR Annually

How we rate this

Delivery Consultant - AI/ML, Professional Services at Amazon rates 86 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Delivery Consultant - AI/ML, Professional Services is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is €56k a year.
The role is based in IT, Milan.
The job was posted on October 16, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGFine-tuningML OpsAI EvaluationComputer visionAI SafetyLangChainLangGraph

Also common in AI consultant jobs at this level

AI agents Prompt engineering React Kubernetes SQL TypeScript

Pay

Typical AI consultant job: $152k

Use the typical AI consultant figure as a reference when pay comes up. See AI consultant jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you decide that one model's output is better than another's for a given task?
Walk me through a computer vision problem you solved, from raw data to a deployed model.

Adapt your resume

List these exact terms on your resume: RAG, Fine-tuning, ML Ops, AI Evaluation, and Computer vision. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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