About the position

The Position

Why Genentech

We're passionate about delivering on Our Promise to improve the lives of patients and create healthier communities for all. We foster a culture of inclusivity, integrity and creativity while boldly pursuing answers to the world's most complex health challenges and transforming society. Genentech's Data, Digital, and Analytics (DDA) team is dedicated to solving complex healthcare challenges and improving patient outcomes. DDA empowers business partners across Commercial, Medical, and Government Affairs (CMG) to make impactful decisions by leveraging data, analytics, and AI/ML to enable fast, targeted actions in rapidly evolving business contexts. DDA fosters a unified understanding of customers, actions, and outcomes by transforming the business insight supply chain from the traditional reactive service model to a modern proactive product model, which integrates analytics and insights seamlessly into CMG's evolving digital, data, and automation platforms, creating scalable solutions and eliminating silos. In DDA, you will work as a trusted, objective advisor and expert, recommending critical decisions and actions to be taken with credibility and a focus on driving measurable impact. You will be part of a diverse, inclusive team that reflects the world we serve, thriving in a welcoming culture built on collaboration and innovation.

The Opportunity

The Sr. Data Scientist - Generative AI Application Specialist is responsible for building fundamental agentic capabilities and high-level business applications within a fast-moving, experimental environment. This role bridges the gap between technical infrastructure and user experience, collaborating with infrastructure teams to design agents and partnering with product owners to ensure optimal development approaches for desired UX. As a subject matter expert, you will stay at the forefront of Generative AI models and capabilities, influencing technical priorities in a complex enterprise environment while representing the team across the global Roche organization.

Responsibilities

• Architect Agentic Systems: Design and build high-level, multi-agent business applications using an extensible infrastructure within a complex, large-scale enterprise environment.
• Drive Technical Innovation: Stay at the forefront of Generative AI and multi-agent systems, integrating cutting-edge models and capabilities to maintain a competitive edge.
• Collaborate on UX & Infrastructure: Partner with product owners and infrastructure teams to bridge capability gaps and align technical development with user experience goals.
• Strategic Leadership & Influence: Shape technical priorities and decision-making processes across the team while identifying systemic issues for senior leadership.
• Global Brand Ambassadorship: Represent the team's interests and expertise across the broader Genentech and global Roche organizations.
• Cultivate AI Literacy: Act as a technical coach to stakeholders and peers, elevating the "AI-savviness" of the organization through mentorship and knowledge sharing.
• Maintain Operational Excellence: Manage high-stakes internal and external partnerships while ensuring all activities strictly adhere to global compliance and regulatory standards.

Requirements

• Bachelor's degree and 5+ years of experience in a relevant field.
• Gen AI Product Expertise: Minimum 3+ years of experience building B2B Generative AI products, specifically focusing on agentic design trade-offs, prompting, and data handling.
• Advanced AI Architecture: Mastery of RAG architecture (including chunking optimization), vector/graph databases, reranking algorithms, and multi-modal application development.
• Framework & Tool Proficiency: Hands-on experience with agentic frameworks (LangChain, LangGraph, AWS Agentcore), MCP/A2A protocols, and modern UI tools like React, Angular, or Figma.
• Systems Optimization & Observability: Expert-level command of observability tools and evaluation methodologies to manage cost, reliability, latency, and performance in agentic systems.
• Technical Communication & Data Skills: Advanced SQL proficiency (including AI-generated SQL) and the ability to translate complex technical analyses for non-technical stakeholders.

Nice-to-haves

• Multimodal Tools: Experience with multimodal Gen AI tools, especially as voice.
• UI Design: Experience designing UI for enterprise software.
• Security Protocols: Experience in security common protocols.
• Industry Experience: Experience in the healthcare, pharmaceutical, or highly regulated industries.
• Enterprise Navigation: Proven ability to influence technical priorities and manage partnerships within a large-scale, global corporate structure.
• Advanced Protocols: Hands-on experience with emerging standards like MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols.
• Prototyping & UX: Familiarity with front-end design workflows (Figma) to ensure AI capabilities translate into