Principal Delivery Consultant- Technical Lead Genai/ml & Data Science, Professional Services, Aws Industries

Amazon Amazon · Big Tech · ZH, Switzerland +1 · Machine Learning Science

Principal Delivery Consultant (Technical Lead) for GenAI/ML & Data Science within AWS Professional Services, focusing on Healthcare and Life Sciences (HCLS) transformation. The role involves defining and owning the technical vision for AI/ML, data platform modernization, and enterprise architecture, advising senior customer executives, and driving AI-native delivery transformations.

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.
  2. Establish operational foundations for agentic AI including multi-model governance, observability, automated guardrails, and secure multi-agent orchestration.
  3. Counsel 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.
  4. Champion responsible AI practices including bias detection, model explainability, and alignment with AWS's AI service guardrails.
  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 technology architecture delivery
  • Leading technical teams
  • AI/ML
  • Enterprise architecture modernization
  • Data architecture and engineering
  • Executive communication
  • Technical leadership of enterprise-wide transformation programs

Nice to have

  • Healthcare and Life Sciences (HCLS) industry depth

What the JD emphasized

  • agentic AI
  • multi-agent orchestration
  • responsible AI practices
  • bias detection
  • model explainability
  • AI-DLC
  • multi-agent systems

Other signals

  • AI/ML
  • Generative AI
  • Agentic AI
  • Large-scale transformation