Guidehouse
Analytics&GenAIArchitect-LifeSciencesTechnology
Neural analysis suggests this role is
optimal for Senior candidates.
“Analytics & GenAI Architect-Life Sciences Technology at Guidehouse. Skills: GenAI, Analytics architecture, Data modeling, AI governance. Design semantic layer architecture. Own semantic layer architecture”
Industry & Context.
Root cause analysis
Travel: None
What They're Looking For.
Must Have
7-10 years of experience, 3 years of experience in Gen AI solution delivery, Python expertise, Experience designing multi-agent topologies, Experience applying structured output and function-calling, Working knowledge of RAG architecture, Experience implementing production-ready practices, Bachelor’s degree in data science, computer science, engineering, or related field
Nice to Have
Experience supporting life sciences analytics domains, Familiarity with AI governance practices in regulated environments, Experience implementing evaluation frameworks for GenAI quality and safety
What You'll Do.
Design semantic layer architecture
Own semantic layer architecture
Support commercial use cases
Translate business requirements
Architect GenAI solutions
Implement GenAI solutions
Establish AI governance standards
Define monitoring benchmarks
Define performance benchmarks
Ensure analytics products are scalable
Ensure analytics products are performant
Align to enterprise data contracts
Align to governance standards
Partner to optimize curated data layers
Collaborate to expose analytics and AI
Contribute reusable accelerators
How You'll Work.
Team & Collaboration
Cloud & Data Platform Architect; Full Stack Architect; Distributed engineering teams
Full Job Description
**_Job Family_ :** Data Science & Analysis (India) **_Travel Required_ :** None ** _Clearance Required_ :** None **Position Summary:** The Analytics & GenAI Architect, Life Sciences Technology, designs and governs analytics and AI-enabled decision solutions that support commercial, market access, patient services, and medical affairs stakeholders. This role owns semantic architecture, KPI mart design, decision product development, and enterprise-grade GenAI orchestration patterns. The architect ensures that analytics and AI solutions are scalable, explainable, production-ready, and aligned to defined business logic. This role operates at the intersection of data engineering, applied AI, and business translation — ensuring decision intelligence products are reliable, governed, and built for sustained enterprise use. **_What You Will Do_ :** * Design and own semantic layer architecture and KPI marts supporting various life sciences commercial use cases (e.g., revenue performance, contracting analytics, engagement strategy, operational effectiveness, forecasting, etc.). * Translate business requirements into structured analytics models, dimensional schemas, and reusable metric definitions. * Architect and implement GenAI solutions using RAG and agentic patterns, including embeddings, vector search, tool integrations, and multi-step workflows. * Establish AI governance standards including evaluation frameworks, versioning practices, guardrails, prompt management, and output validation controls. * Define monitoring, telemetry, and performance benchmarks for analytics pipelines and GenAI workloads. * Ensure analytics products are scalable, performant, and aligned to enterprise data contracts and governance standards. * Partner with Cloud & Data Platform Architect to optimize curated data layers for advanced analytics and AI grounding. * Collaborate with Full Stack Architect to expose analytics and AI through secure, performant APIs and user experiences. * Contribute reusa
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