Principal Delivery Consultant – AI ML, 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.
• Set reference architectures, re-usable patterns, and technical standards that ensure coherence across 50+ AWS, partner, and customer builders.
• 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 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

• Knowledge of compliance and security standards across the enterprise IT landscape.
• 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.
• Experience 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.
• Influence and align customer enterprise architects and partner technical teams on architecture patterns and technology choices in multi-vendor environments.