AI Architect – Life Sciences (Commercial Analytics & GenAI

We are seeking a highly experienced AI Architect to lead the design and implementation of enterprise-scale AI/GenAI solutions for Life Sciences Commercial Operations. This role will focus on building scalable, secure, and business-driven AI platforms leveraging AWS Bedrock, Databricks (including Genie), and enterprise Copilot frameworks, along with deep integration of pharma commercial datasets (IQVIA, Symphony, patient, claims, Veeva CRM, and digital data).

The ideal candidate brings a strong combination of GenAI architecture expertise and Life Sciences commercial domain knowledge.

Design and implement GenAI-powered solutions using:

• AWS Bedrock (foundation models, agents, RAG architectures)
• Databricks Lakehouse & Genie (semantic layer, AI-assisted querying)
• Enterprise Copilot solutions integrated into business workflows

Define reference architectures for:

• Conversational analytics platforms
• Automated reporting and summarization
• Next-best-action and recommendation engines

Architect end-to-end data pipelines integrating:

• Patient and claims data (open & closed claims)
• Digital marketing and engagement platforms

Enable data harmonization, semantic modeling, and AI-ready datasets

Leverage Databricks (Delta Lake, Spark) and AWS-native services

Drive high-value use cases such as:

• HCP targeting, segmentation, and profiling
• Sales force effectiveness analytics
• Patient journey and adherence insights
• Market access and payer analytics

Develop RAG-based solutions combining structured and unstructured data

Build AI copilots for business users (brand teams, field force, market access)

Ensure compliance with:

• HIPAA and global data privacy regulations

Implement Responsible AI practices

Define data security, lineage, and access governance frameworks

Collaborate with:

• Commercial stakeholders (Sales, Marketing, Market Access)
• Data engineering and analytics teams
• Enterprise architecture teams

Translate business needs into AI solution roadmaps and architectures

Support solutioning, proposals, and client engagements

• 10–15+ years in data, analytics, or AI architecture
• 5+ years in Life Sciences Commercial domain
• Hands-on experience with:
• IQVIA, Symphony, Claims and Patient datasets
• Veeva CRM and commercial data ecosystems

AI/GenAI Platforms:

• AWS Bedrock (mandatory)

Programming:

• Python, PySpark, SQL

• LLMs, RAG architectures, embeddings, vector search
• NLP and conversational AI systems

Cloud:

• Strong expertise in AWS ecosystem
• API-based integration and scalable microservices design

• Experience building AI copilots or conversational assistants at scale
• Familiarity with:
• Salesforce Data Cloud / Data 360
• Digital marketing platforms
• Experience with LLMOps / MLOps frameworks
• Knowledge of patient analytics and real-world data (RWD/RWE)

• Ability to influence cross-functional stakeholders
• Experience leading architecture reviews and governance forums
• Outcome-driven mindset focused on business impact
• Production-grade AI solutions
• Commercial AI use case roadmap