AI Architect- Pharmaceutical Domain

Company Description

USM Business Systems is a global technology services provider helping organizations transform their business models through AI, automation, and advanced digital solutions. Established in 1999 in the Washington DC metro area, USM now operates with over 1000 partners across North America, Europe, Asia, and Australia. The company delivers services including Automation & Innovation, Architecture & Consulting, Maintenance & Support, and Contingent Workforce solutions. USM specializes in critical areas such as AI, data science, RPA, IoT, blockchain, mobile commerce, and enterprise data management to drive agility, competitiveness, and profitability for clients. Its experts design enterprise architectures, build and deploy applications, and support IT operations around the clock.

Note: This is for one of our direct client.

Hybrid- 3 days from Office

Location: Santa Monica, CA

Contract:- 12 Months

Role Description

The AI Architect role is a 12 month Contract position based in Santa Monica, CA. The AI Architect will design and oversee end-to-end AI solution architectures, ensuring scalability, security, and integration with existing enterprise systems. Day-to-day responsibilities include collaborating with stakeholders to understand business requirements, selecting appropriate AI and data technologies, and guiding the design of models, data pipelines, and APIs. The role involves working closely with software development teams to translate architectural blueprints into implementable solutions, conducting technical reviews, and ensuring adherence to best practices and compliance standards. The AI Architect will also mentor team members, contribute to governance frameworks, and support the continuous improvement of USM’s AI and automation offerings.

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 .

Key Responsibilities

• AI / GenAI Architecture
• 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
• Intelligent commercial insights assistants
• Automated reporting and summarization
• Next-best-action and recommendation engines

Data & Platform Engineering

• IQVIA data (Xponent, LAAD, etc.)
• Symphony datasets
• Patient and claims data (open & closed claims)
• Veeva CRM data
• Digital marketing and engagement platforms
• Enable data harmonization, semantic modeling, and AI-ready datasets
• Leverage Databricks (Delta Lake, Spark) and AWS-native services

Advanced Analytics & AI Use Cases

• HCP targeting, segmentation, and profiling
• Omnichannel engagement optimization
• 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)

Governance, Security, and Compliance

Ensure compliance with

• HIPAA and global data privacy regulations
• Implement Responsible AI practices
• Define data security, lineage, and access governance frameworks

Stakeholder Engagement

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

Required Qualifications

Experience

• 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

Technical Skills

AI/GenAI Platforms

• AWS Bedrock (mandatory)
• Databricks (Lakehouse, ML, Genie)
• Enterprise Copilot frameworks

Programming

Python, PySpark, SQL

AI Techniques

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

Cloud

• Strong expertise in AWS ecosystem

Architecture Expertise

• Enterprise AI architecture design
• Data modeling (semantic layers, ontologies)
• API-based integration and scalable microservices design

Preferred Qualifications

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

Leadership & Soft Skills

• Strong executive communication skills
• Ability to influence cross-functional stakeholders
• Experience leading architecture reviews and governance forums
• Outcome-driven mindset focused on business impact

Key Deliverables

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

Interested candidates can share your updated CV with ***email_hidden***

Note:- Pharmaceutical domain experience is mandatory and one should work in the latest projects.

Regard's

Praveen Shyam