AI Architect

About the role

Lead enterprise-scale AI/GenAI solutions for Pharma Commercial Ops. Build secure, scalable platforms using AWS Bedrock, Databricks (Genie), Copilot frameworks, integrated with IQVIA, Symphony, Patient/Claims, Veeva CRM & Digital data.

Responsibilities

• AI/GenAI Architecture: Design GenAI solutions on AWS Bedrock (RAG, Agents, FMs), Databricks Lakehouse/Genie, Enterprise Copilots. Architectures for conversational analytics, insights assistants, auto-reporting, N-B-A engines.
• Data Engineering: Build E2E pipelines for IQVIA (Xponent, LAAD), Symphony, Open/Closed Claims, Veeva CRM, Digital. Data harmonization, semantic modeling, Delta Lake/Spark.
• Use Cases: HCP targeting/segmentation, omnichannel optimization, field force effectiveness, patient journey/adherence, market access/payer analytics, RAG + copilots for brand/field teams.
• Governance: HIPAA, privacy, Responsible AI, data security, lineage & access controls.
• Stakeholders: Partner with Sales, Marketing, Market Access, Data & EA teams. Translate business needs to AI roadmaps, support solutioning & client engagements.

Requirements

• 10-15+ years in Data/AI Architecture
• 5+ years in Life Sciences Commercial
• Hands-on with IQVIA, Symphony, Claims/Patient data, Veeva
• AWS Bedrock (mandatory), Databricks, Copilot
• Python, PySpark, SQL
• LLMs, RAG, embeddings, vector search, NLP
• Strong AWS

Preferred

• AI copilots at scale
• Salesforce Data Cloud/Data 360
• Digital marketing platforms
• LLMOps/MLOps
• RWD/RWE

Deliverables

• AI/GenAI blueprints
• Production-grade AI solutions
• Commercial AI roadmap
• Reusable accelerators (RAG, copilots, semantic layers)