Senior Data Scientist, Gen AI Application

Roche • South San Francisco, CA

1d • $177,310 - $329,290 • Hybrid

About The Position

As a Senior Data Scientist - Generative AI Applications within Genentech’s Data, Digital, and Analytics (DDA) organization, this role bridges core AI infrastructure and business applications across Commercial, Medical, and Government Affairs (CMG). The position designs, builds, and optimizes intelligent agents and agentic workflows that reason, use complex tools, and automate multi-step business processes. It partners with platform engineers and business product owners to deliver seamless, reliable, user-centric GenAI solutions with measurable business impact.

The role architects and deploys AI agents, orchestration workflows, decision logic, and collaboration patterns; establishes tool schemas, APIs, permissions, error handling, and human escalation paths; and optimizes agent accuracy, task reliability, latency, cost efficiency, and user experience. It also develops memory, context-retention, retrieval-augmented generation, and summarization strategies; establishes evaluation frameworks and observability; integrates agentic systems into secure production environments; and standardizes agent development practices across DDA.

The position is based in South San Francisco and follows a hybrid schedule, with three days per week on campus. Relocation benefits are not available. The expected salary range for the California primary location is $177,310–$329,290. Actual pay depends on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. The position also qualifies for the benefits described through the linked benefits information.

Requirements

• At least 5 years of professional experience in software engineering, machine learning, or GenAI application development with a bachelor's degree, or equivalent education and experience (for example, a master's degree plus 3 years of work experience).
• Hands-on experience designing, building, and deploying LLM-powered agents or agentic workflows in production environments.
• Strong working knowledge of prompting techniques, tool calling, structured outputs, planning mechanisms, RAG, and context management.
• Proficiency in Python, TypeScript, or a comparable production language, and experience with agent orchestration frameworks such as LangGraph, LangChain, or custom frameworks.
• Demonstrated expertise designing APIs, tool contracts, asynchronous workflows, and integration patterns for scalable systems.

Nice To Haves

• Experience with multi-agent architecture systems and inter-agent communication protocols such as A2A and MCP.
• Experience building and deploying agentic workflows within enterprise platforms or regulated industries such as biotech, pharma, finance, or healthcare.
• Familiarity with model routing, prompt versioning, fine-tuning, guardrails, and human-in-the-loop workflows.
• Strong understanding of cloud environments, including AWS and AWS AgentCore, identity and access management, data privacy, and secure tool execution.
• Proven track record translating ambiguous business objectives into reliable technical agent workflows and quantifiable outcomes.

Responsibilities

• Architect, build, and deploy intelligent AI agents, orchestration workflows, decision logic, and collaboration patterns for complex enterprise applications.
• Define and implement tool schemas, APIs, permissions, error-handling mechanisms, and human-in-the-loop escalation paths for agentic systems.
• Optimize agent accuracy, task-completion reliability, latency, cost efficiency, and end-user experience.
• Design memory, context-retention, retrieval-augmented generation (RAG), and summarization strategies.
• Establish evaluation frameworks, observability metrics, synthetic test scenarios, and trace analyses to diagnose failure modes and prevent hallucinations.
• Partner with application engineers, platform teams, and business product managers to integrate agentic systems into secure, production-grade enterprise environments.
• Standardize agent development patterns, guardrails, and best practices across the DDA organization.

Benefits

• A discretionary annual bonus may be available based on individual and Company performance.
• The position qualifies for the benefits detailed through the benefits link.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior