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

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.


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.

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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

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