This role pays less than
76%
of similar roles. Most pay
$188,981–$270,739
— the shaded band above.
At the midpoint, this role pays about
$187k
versus about
$230k
for comparable roles.
Based on 239 similar postings.
Employer
About Bristol Myers Squibb
Bristol Myers Squibb is a global biopharmaceutical company committed to discovering, developing and delivering innovative medicines to patients.
Bristol Myers Squibb currently has
33 open roles
on FindRole.
Listed pay typically runs
$125,480–$152,049
across 33 roles with salary data.
Associate Director, Rewire Field Experience and Agentic AI Architect
The Associate Director, Rewire Field Experience and Agentic AI Architect leads the architectural design for the core Rewire Field agentic experience, creating a unified flow of work for field users by integrating CRM systems, field intelligence, and AI agents. This role involves defining technical blueprints for components like the AI Prep Agent, Field Intelligence Dashboard, and HCP-Facing AI Agents while ensuring seamless integration with Veeva Vault CRM, Databricks, and various orchestration services. The architect must establish patterns for contextual reasoning, workflow execution, and automated actions to reduce administrative burdens. Key responsibilities include managing architecture standards, making build-versus-buy decisions, and ensuring compliance with privacy and security protocols. The role requires expertise in agentic AI, generative AI, API integration, and cloud platforms like Azure or AWS within a highly regulated pharmaceutical environment.
Define and maintain the end-to-end IT architecture for the core Rewire Field agentic experience across data, security, and integration layers.
Design a unified flow that integrates AI Prep, Field Intelligence, and Post-Call agents into one seamless pre-call and post-call journey.
Establish technical patterns to transform raw insights and orchestration outputs into actionable field intelligence for users.
Define integration points and data contracts between the core experience and partner systems like coaching and performance tracking platforms.
Own architectural decisions, standards, and build-versus-buy recommendations while maintaining solution blueprints and interface contracts.
Embed cybersecurity, privacy, and responsible AI requirements into the architecture to ensure compliant and traceable agentic workflows.
Translate high-level architecture concepts into actionable technical components, user stories, and delivery plans for engineering teams.
Establish feedback loops with field users to validate architectural choices through prototypes and measurable success metrics.
What we're looking for
Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field.
Minimum 8 years of experience in enterprise solution architecture, commercial technology, AI architecture, digital product architecture, or field-facing technology.
Experience designing connected enterprise experiences across multiple applications, data sources, workflows, and user interfaces.
Strong understanding of agentic AI, generative AI, contextual reasoning, AI orchestration, workflow automation, and human-in-the-loop design.
Proficiency with CRM and commercial platforms, specifically Veeva Vault CRM, Veeva Commercial Cloud, Salesforce, or similar systems.
Knowledge of APIs, event-driven architecture, middleware, data products, master data, real-time integrations, identity, and authorization.
Experience with cloud, data, and AI platforms such as Databricks, Azure, AWS, OpenAI, or equivalent technologies.
Experience in highly regulated industries like pharmaceuticals, biotechnology, or medical devices including knowledge of privacy, cybersecurity, and responsible AI.
LLMs
Agent Frameworks
RAG
Vector Databases
Python
Prompt Engineering
Machine Learning
Deep Learning
Cloud-native Development
APIs
Data Science
Statistical Analysis
Time Series Analysis
Data Visualization
Observability
Agentic AI
Heterogeneous Computing
ROCm
AMD Enterprise AI
AMD Zen Software Studio
LLM Inference
RAG
SGLang
LMCache
x86
ARM
Distributed Systems
Confidential Computing
Performance Engineering
Multi-agent Systems
Networking