Senior Delivery Consultant – (AI/ML Specialist), Telecommunications, AWS Professional Services

Amazon is hiring a Senior Delivery Consultant – (AI/ML Specialist), Telecommunications, AWS Professional Services in Zurich, Switzerland. Level rates it ; you can apply on Level.

AI in this role

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The Amazon Web Services Professional Services (AWS ProServe) Telco organization is looking for a senior, experienced, and highly motivated business-oriented AI/ML practitioner who possesses a unique balance of executive advisory capability, business acumen, and deep technical expertise across Generative AI, Agentic AI, and Machine Learning, with proven experience leading large-scale cloud-based transformations and implementations.

AWS ProServe engages in a wide variety of strategic projects for customers and partners, bringing together AWS customer experience, best practices, and technical expertise to help organizations accelerate innovation and business outcomes. Our team collaborates across the broader AWS organization to provide customers access to product, engineering, service, and training teams, delivering scalable solutions and driving feature innovation across industries.

This role will focus on advising enterprise customers on how to transform business and operational outcomes through the adoption of Generative AI, Agentic AI, and Machine Learning on AWS. As a Consultant, you will act as a trusted advisor to senior business and technology leaders, shape AI and cloud transformation strategies, lead complex engagements, guide architecture best practices, and oversee the successful delivery of large-scale AI/ML and GenAI implementations with customers and partners. You will also help drive thought leadership, mentor delivery teams, and influence the evolution of AWS AI/ML professional services capabilities across the region.

Key job responsibilities
- Advise customer technologists and business leaders on the art of the possible with Generative AI, Agentic AI, and Machine Learning, helping them design scalable AI solutions on AWS that deliver measurable business value
- Discuss complex industry-specific business and technology concepts with senior customer stakeholders, particularly across Telecommunications industry
- Lead executive and technical workshops with customers to identify transformation opportunities and define how Generative AI, Agentic AI, and Machine Learning can accelerate business outcomes
- Drive large and complex customer engagements across pre-sales and delivery, from ideation and strategy through architecture design, scoping, execution, and successful delivery outcomes
- Provide technical leadership and delivery oversight across customer engagements to ensure alignment on scope, architecture, deliverables, timelines, risks, and expected business outcomes
- Act as a trusted advisor to senior customer stakeholders, guiding AI and cloud transformation initiatives while balancing business priorities, governance, scalability, and operational readiness
- Mentor consultants and delivery teams by promoting AWS best practices, reusable patterns, and high standards of technical and delivery excellence across engagements

221100

A day in the life
You'll partner with customers' architecture and engineering teams to solve industry-complex challenges — for example, bringing live/uncompressed video workflows to the cloud, or modernising a media supply chain. A typical day blends hands-on architecture and prototyping, whiteboarding with customer stakeholders, collaborating with AWS service and partner teams, and writing narratives that align business outcomes with technical delivery. You will move fluidly between tactical delivery and strategic influence, often leading across multiple workstreams and diverse groups, and managing escalations with ease. Internal stakeholders include AWS account teams, service teams, and partners; your customers are leading telecommunication organisations transforming their operations on AWS.

About the team
About AWS
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 Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

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 in the cloud.

Basic qualifications

- 5+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of customer-facing work, engaging with customer executives, technologists or partners to solve business problems with advanced technologies experience
- 4+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- 3+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python)

Preferred qualifications

- 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
- 5+ 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 Telecommunications industry

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.

How we rate this

Senior Delivery Consultant – (AI/ML Specialist), Telecommunications, AWS Professional Services at Amazon rates 68 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● 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

Senior Delivery Consultant – (AI/ML Specialist), Telecommunications, AWS Professional Services is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in CH, ZH, Zurich.
The job was posted on October 14, 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

AI agentsML OpsComputer visionLangChainLlamaIndexLangGraphBedrockPyTorch

Also common in AI consultant jobs at this level

RAG LLM Prompt engineering Databricks Vector databases Azure

Pay

Typical AI consultant job: $152k

This posting doesn't list pay. Use the typical AI consultant figure when pay comes up. See AI consultant jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What's a project where you used LangChain hands-on?
Walk me through how you've used LlamaIndex in your day-to-day work.

Adapt your resume

List these exact terms on your resume: AI agents, ML Ops, Computer vision, LangChain, and LlamaIndex. 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.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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