Principal Delivery Consultant- Technical Lead GenAI/ML & Data Science, Professional Services, AWS Industries

Amazon is hiring a Principal Delivery Consultant- Technical Lead GenAI/ML & Data Science, Professional Services, AWS Industries in Zurich, Switzerland. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this AI consultant role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Bedrock, RAG and AI safety.
Level classifies it as a lead role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

bedrock

ragai-safety

The Amazon Web Services Professional Services (ProServe) team is seeking a Principal Delivery Consultant to serve as a technical leader for large-scale Healthcare and Life Sciences (HCLS) transformation programs. In this role as an individual contributor, you will define and own the technical vision across several concurrent workstreams spanning AI/ML, data platform modernization, and enterprise architecture. This is a pivotal leadership role that will shape how the leading global HCLS companies drive business value from AI and cloud computing.
You will bring a "T-shaped" profile: broad proficiency across AI/ML, enterprise architecture modernization, and data architecture and engineering, paired with distinctive expertise in one of these technical areas. You will combine deep technical depth with the ability to counsel senior customer executives (VP+) on major technology choices, blending technical rigor with effective framing of business considerations.

The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives.
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Key job responsibilities
Enterprise Architecture Ownership & Technical Standards: Define and own the end-to-end technical architecture for large-scale HCLS transformation programs, setting reference architectures, re-usable patterns, and technical standards that ensure coherence across 50+ AWS, partner, and customer builders. Establish operational foundations for agentic AI including multi-model governance, observability, automated guardrails, and secure multi-agent orchestration.
Executive Technical Advisory & Decision Shaping: Bridge the gap between customer enterprise architects' expectations and pragmatic delivery, counseling executives on major technology choices (total cost of ownership, time-to-value, build vs. buy) and influencing technical decisions across customer and partner teams without direct authority, earning credibility through depth and clarity.
Cross-Team Alignment & Architectural Governance: Drive alignment across teams with sometimes diverse technical opinions, resolve architectural conflicts, adapt architecture mid-flight as program needs evolve, and coach engineers across partner organizations who do not directly report to you, raising the technical bar across the entire delivery organization. Champion responsible AI practices including bias detection, model explainability, and alignment with AWS's AI service guardrails.
AI/ML, Data & Knowledge Architecture: Continuously grow expertise across AI/ML, enterprise architecture, and data engineering and industry depth in HCLS, maintaining knowledge at the frontier of AWS service innovations, prescriptive guidance (e.g. Well-Architected Agentic AI Lens, Generative AI Lifecycle framework, and AI-DLC methodology), and translating those innovations into the specific HCLS customer context.
AI-Native Delivery Transformation: Drive AI-DLC (AI-Driven Development Life Cycle) methodologies across the delivery organization, redesigning delivery models for accelerated scale and pace, steering multi-agent systems at scale using patterns such as supervisor-worker hierarchies, workflow orchestration, and saga orchestration as defined in AWS prescriptive guidance, and embedding AI-native workflows into program execution to maximize builder productivity, to achieve step-change improvements in builder productivity and time-to-value.

About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, 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 pioneeredcloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companiestrust 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 (diversity) 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

- 8+ years of experience in enterprise technology architecture delivery, with at least 5 years leading technical teams defining and governing technical architecture on complex transformation programs
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- Depth in one or more of the following technical areas: AI/ML, enterprise architecture modernization, or data architecture and engineering, demonstrated through technical leadership of enterprise-wide transformation programs at leading global enterprises
- Strong executive communication skills, with ability to present architecture trade-offs, risk assessments, and recommendations to VP+ audiences with clarity and confidence
- Demonstrated ability to adopt and champion emerging delivery methodologies that accelerate team productivity and time-to-value

Preferred qualifications

- AWS Professional-level certifications (e.g., GenAI Developer Professional, Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty)
- Experience in the healthcare and life sciences industry, with emphasis on large biopharma, large medtech, and payer customers. Experience designing AI solutions that meet regulatory requirements (HIPAA, GxP, 21 CFR Part 11) and meet standards like OMOP, CDISC, FHIR, and HL7 FHIR R4
- Experience re-designing delivery workflows to become AI-native, including steering and validating multi-agent systems at scale to drive delivery productivity and accelerate time-to-value
- Demonstrated expertise in designing and operationalizing agentic AI systems using patterns such as multi-agent orchestration, tool-use agents, and workflow orchestration — ideally leveraging AWS services (Amazon Bedrock, AgentCore)
- Experience designing data platforms at scale, including data lakes, lakehouses, knowledge graphs, vector databases, RAG (Retrieval-Augmented Generation) architectures, and ontology-driven architectures
- Experience influencing and aligning customer enterprise architects and partner technical teams on architecture patterns and technology choices in multi-vendor environments

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

Principal Delivery Consultant- Technical Lead GenAI/ML & Data Science, Professional Services, AWS Industries 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal Delivery Consultant- Technical Lead GenAI/ML & Data Science, Professional Services, AWS Industries 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 July 20, 2026.
Seniority: lead.
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

RAGAI SafetyBedrock

Also common in AI consultant jobs at this level

AI agents Python LLM SQL Prompt engineering Azure

Pay

Typical AI consultant job: $151k

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 would you design a retrieval step so the model answers from real data instead of guessing?
How do you think about the risk of an AI system in this kind of role failing silently?
What are the limits of Bedrock that you've run into, and how did you work around them?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: RAG, AI Safety, and Bedrock. 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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