Senior Data Scientist, Gen AI Application
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 works closely with platform engineers and business product owners to deliver reliable, user-centric GenAI solutions with measurable business impact. The role is based in South San Francisco, with a hybrid schedule requiring three days per week on campus. No relocation benefits are available. The expected salary range for the primary location in California 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 qualifies for the benefits described through the employer’s benefits information.
Requirements
- At least 5 years of professional experience in software engineering, machine learning, or GenAI application development.
- 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 or 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 such as AWS and AWS AgentCore, identity and access management, data privacy, and secure tool execution.
- Proven track record of 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 behavior for accuracy, task-completion reliability, latency, cost efficiency, and end-user experience.
- Design memory, context-retention, retrieval-augmented generation (RAG), and summarization strategies to enhance agent capabilities.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
