Analytics & GenAI Architect-Life Sciences Technology

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Clearance Required:

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 reusable accelerators including KPI templates semantic models evaluation harnesses and RAG reference architectures.

What You Will Need:

• 710 years of experience in analytics engineering BI architecture data science with at least 3 years of experience in Gen AI solution delivery.
• Strong expertise in Python with experience building scalable AI and analytical models.
• Experience designing multi-agent topologies (supervisorworker router debate) with explicit planning memory and tool-use policies. Experience applying structured output and function-calling.
• Working knowledge of RAG architecture vector search embeddings and reliable orchestration.
• Experience implementing advanced planning and reasoning patterns (React-style tool reasoning task decomposition dynamic routing) with guardrails for prompt injection data leakage and tool misuse.
• Expertise in Agentic AI frameworks leveraging LangChain and LangGraph. Knowledge of MCP servers and tool integration.
• Experience implementing production-ready practices including testing monitoring CI/CD integration and observability.
• Experience collaborating across distributed engineering teams.
• Bachelors degree in data science computer science engineering or related field.

What Would Be Nice To Have:

• Experience supporting life sciences analytics domains (e.g. contracting performance analytics incentive compensation omnichannel strategy).
• Familiarity with AI governance practices in regulated environments.
• Experience implementing evaluation frameworks for GenAI quality and safety.

What We Offer:

Guidehouse offers a comprehensive total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

About Guidehouse

Guidehouse is an Equal Opportunity EmployerProtected Veterans Individuals with Disabilities or any other basis protected by law ordinance or regulation.

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