Principal Delivery Consultant – Modernization, Professional Services, AWSI HCLS

About the role

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.

Responsibilities

• Define and own the technical vision across several concurrent workstreams spanning AI/ML, data platform modernization, and enterprise architecture.
• Establish operational foundations for agentic AI including multi-model governance, observability, automated guardrails, and secure multi-agent orchestration.
• 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.
• 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.
• 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.
• 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.
• Design and operationalize agentic AI systems using patterns such as multi-agent orchestration, tool-use agents, and workflow orchestration — ideally leveraging AWS services (Amazon Bedrock, AgentCore).
• Design data platforms at scale, including data lakes, lakehouses, knowledge graphs, vector databases, RAG (Retrieval-Augmented Generation) architectures, and ontology-driven architectures.
• Influence and align customer enterprise architects and partner technical teams on architecture patterns and technology choices in multi-vendor environments.

Requirements

• Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience.
• Experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation.
• Experience working with fast-moving, high-performance teams and driving innovative solutions tailored to unique business environments.
• 8+ years of experience in enterprise technology architecture delivery, with at least 5 years influencing technical teams and defining and governing technical architecture on complex transformation programs.
• 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.

Qualifications

• Basic Qualifications: 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.
• Preferred Qualifications: AWS Professional-level certifications (e.g., GenAI Developer Professional, Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty).