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Amazon Web Services (AWS)

Principal Delivery Consultant – AI ML, Professional Services, AWSI HCLS

austin, TX

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Job description

Description

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.

Description

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. This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S.

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

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Worksite address

austin, TX, 78716, US

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