Senior Delivery Consultant – Modernization, Professional Services, Awsi Hcls

Amazon Amazon · Big Tech · Boston, MA · Solutions Architect

Senior Delivery Consultant for AWS Professional Services focusing on Healthcare and Life Sciences (HCLS) transformation programs. The role involves defining and owning the technical vision across AI/ML, data platform modernization, and enterprise architecture. Key responsibilities include establishing enterprise architecture, providing executive technical advisory, driving cross-team alignment, architecting AI/ML and data solutions, and transforming delivery models using AI-native methodologies and multi-agent systems.

What you'd actually do

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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

Skills

Required

  • Enterprise Architecture
  • AI/ML
  • Data Architecture
  • Data Engineering
  • Technical Leadership
  • Executive Advisory
  • Program Management
  • Cloud Computing (AWS)
  • Healthcare and Life Sciences (HCLS) industry knowledge
  • Responsible AI practices
  • Bias detection
  • Model explainability
  • Agentic AI
  • Multi-model governance
  • Automated guardrails
  • Secure multi-agent orchestration
  • Workflow orchestration
  • Supervisor-worker hierarchies

Nice to have

  • Generative AI Lifecycle framework
  • AI-DLC methodology
  • Well-Architected Agentic AI Lens

What the JD emphasized

  • technical leader for large-scale Healthcare and Life Sciences (HCLS) transformation programs
  • define and own the technical vision across several concurrent workstreams spanning AI/ML, data platform modernization, and enterprise architecture
  • shape how the leading global HCLS companies drive business value from AI and cloud computing
  • broad proficiency across AI/ML, enterprise architecture modernization, and data architecture and engineering, paired with distinctive expertise in one of these technical areas
  • deep technical depth with the ability to counsel senior customer executives (VP+) on major technology choices
  • Define and own the end-to-end technical architecture for large-scale HCLS transformation programs
  • Establish operational foundations for agentic AI including multi-model governance, observability, automated guardrails, and secure multi-agent orchestration
  • counseling executives on major technology choices (total cost of ownership, time-to-value, build vs. buy)
  • influencing technical decisions across customer and partner teams without direct authority
  • Drive alignment across teams with sometimes diverse technical opinions
  • resolve architectural conflicts
  • adapt architecture mid-flight as program needs evolve
  • coach engineers across partner organizations who do not directly report to you
  • 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)
  • 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
  • embedding AI-native workflows into program execution to maximize builder productivity
  • achieve step-change improvements in builder productivity and time-to-value
  • 7+ years of professional or military 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
  • 5+ years of experience in enterprise technology architecture delivery, with experience influencing technical teams and defining and governing technical architecture on complex transformation programs

Other signals

  • AI/ML transformation programs
  • agentic AI
  • multi-model governance
  • automated guardrails
  • secure multi-agent orchestration
  • responsible AI practices
  • bias detection
  • model explainability
  • Generative AI Lifecycle framework
  • AI-DLC methodology
  • multi-agent systems at scale
  • workflow orchestration
  • supervisor-worker hierarchies