Sr. Principal Scientific Product Specialist, AI

Simulations Plus

13d•Remote

About The Position

Simulations Plus stands as a premier provider in the biopharma sector, offering advanced software and consulting services that enhance drug discovery, development, research, clinical trial operations, regulatory submissions, and commercialization. Our comprehensive biosimulation solutions integrate artificial intelligence/machine learning, physiologically based pharmacokinetics, physiologically based biopharmaceutics, quantitative systems pharmacology/toxicology, and population PK/PD modeling approaches. We also deliver simulation-enabled performance and intelligence solutions alongside medical communications support for clinical and commercial drug development. Our cutting-edge technology is licensed and utilized by leading pharmaceutical, biotechnology, and regulatory agencies worldwide. Leadership truly cares about maintaining a positive culture and employee well-being. We offer fully remote work, flexible schedules, and generous vacation policy along with affordable health coverage, stock options, annual bonus, and more! Check out how much our employees love working here: https://www.comparably.com/companies/simulations-plus [https://www.comparably.com/companies/simulations-plus]. The Senior Principal Product Enablement Specialist, AI will serve as a senior technical enablement expert responsible for enabling AI-powered platform capabilities across the Simulations Plus ecosystem. This role focuses on the enablement, implementation, and operational readiness of AI agents, AI-assisted workflows, and the composition layer that supports cross-product functionality. The role combines deep expertise in AI systems, product enablement, and enterprise software implementation to ensure that AI capabilities are successfully integrated, tested, documented, and supported across the product portfolio. This individual contributor role provides the opportunity to shape how AI capabilities are delivered and adopted across products while remaining hands-on with implementation, testing, and customer enablement.

Requirements

AI Systems Expertise
7+ years of experience working with AI-enabled software products or AI platforms
experience implementing LLM-based systems, AI agents, or AI pipelines
experience with evaluation frameworks for AI outputs
Strong understanding of AI reliability, monitoring, and operational practices
Ability to translate AI capabilities into practical product functionality
Technical Implementation Skills
Experience implementing complex software systems or platform capabilities
working with APIs and distributed services
integrating new platform capabilities into existing applications
Strong programming or scripting experience
Python or similar languages commonly used in AI development
Experience working with modern AI tooling and development frameworks
Product Enablement and Delivery Experience
Experience enabling complex software products through
implementation
testing and validation
documentation
training and support
Demonstrated ability to support multiple product environments simultaneously
Ability to translate technical concepts into practical guidance for users and teams
Communication and Collaboration
Strong technical communication and documentation skills
Ability to collaborate effectively with product, engineering, and operations teams
Experience influencing cross-functional teams without direct authority
Strong organizational skills and ability to manage multiple initiatives

Nice To Haves

AI Platform and Agent Architectures
Experience working with AI agent architectures and orchestration frameworks
multi-agent systems
tool-based agent workflows
Experience implementing retrieval-augmented generation or knowledge-based AI systems
Familiarity with AI evaluation pipelines and observability tooling
Enterprise AI Deployment
Experience deploying AI capabilities in enterprise software environments
reliability and monitoring practices
performance optimization for AI services
Experience integrating AI capabilities into existing products or platforms
Familiarity with cloud-based AI infrastructure and deployment models
Platform and Ecosystem Experience
Experience supporting cross-product platforms or shared services
Understanding of API-based product architectures
Familiarity with software platforms that support multiple products or services

Responsibilities

AI Product Enablement Leadership
Define and establish enablement best practices for AI-powered capabilities across the ecosystem
AI composition layer integration
shared AI agents (e.g., data agents, reporting agents)
cross-product AI workflows
Develop implementation frameworks for deploying AI capabilities consistently across products
Establish standards for AI feature testing, validation, and operational readiness
Create reusable implementation patterns and configuration templates for AI capabilities
Drive standardization of AI documentation, enablement materials, and training resources
AI Capability Implementation
Implement AI agents and AI-assisted features within product workflows
integrate AI agents with product APIs and services
configure AI pipelines and execution environments
adapt shared AI capabilities to product-specific contexts
Collaborate with engineering and product teams to operationalize AI features
Support integration of shared AI services into multiple product environments
Identify and resolve implementation challenges during development and deployment
Ensure AI features function consistently across the product ecosystem
AI Feature Testing and Validation
Develop and execute testing frameworks for AI-powered product capabilities
functional testing of AI agents
evaluation pipelines for AI outputs
reliability and performance testing
Implement human-in-the-loop validation strategies for AI-assisted workflows
Identify edge cases and failure modes in AI-driven features
Work with engineering teams to improve reliability and monitoring of AI systems
Establish quality assurance practices specific to AI-enabled product features
Documentation and Training
Develop comprehensive documentation for AI-enabled product capabilities
architecture and usage documentation
implementation and integration guides
troubleshooting resources
Create training curricula for internal teams and customers adopting AI capabilities
Produce educational materials explaining AI workflows and agent capabilities
Ensure documentation remains aligned with evolving AI platform capabilities
Support onboarding and training of teams implementing AI-powered workflows
Operational Support and Troubleshooting
Serve as a technical escalation point for complex AI feature deployments
Diagnose and resolve issues related to AI agents, pipelines, and workflows
Support services and support teams in troubleshooting AI-enabled functionality
Identify patterns in operational issues to improve AI reliability and usability
Contribute improvements to operational practices for AI-powered features
Cross-Product Collaboration
Collaborate with Product and Engineering teams to ensure consistent AI capability delivery
Work with Services and Support teams to capture operational insights from AI deployments
Provide feedback to product teams on usability and adoption challenges
Identify opportunities to reuse AI capabilities across products and workflows
Help maintain alignment between AI platform capabilities and product-level implementations