Senior Data Scientist, Gen AI Application
About The Position
As a Sr. Data Scientist - Generative AI Applications within Genentech’s Data, Digital, and Analytics (DDA) organization, you will bridge the gap between core AI infrastructure and high-impact business applications across Commercial, Medical, and Government Affairs (CMG). In this high-visibility role, you will design, build, and optimize intelligent agents and agentic workflows that reason, utilize complex tools, and automate intricate multi-step business processes. You will collaborate closely with platform engineers and business product owners to deliver seamless, reliable, and user-centric GenAI solutions that drive measurable business impact.
Requirements
- 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, alongside experience with agent orchestration frameworks (e.g., 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 (e.g., A2A, MCP).
- Experience building and deploying agentic workflows within enterprise platforms or regulated industries (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 (AWS, AWS AgentCore), identity, 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 robust tool schemas, APIs, permissions, error-handling mechanisms, and human-in-the-loop escalation paths for agentic systems.
- Optimize agent behavior across key metrics including accuracy, task completion reliability, latency, cost efficiency, and end-user experience.
- Design effective memory, context retention, retrieval-augmented generation (RAG), and summarization strategies to enhance agent capabilities.
- Establish comprehensive 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
- Discretionary annual bonus may be available based on individual and Company performance.
- Benefits detailed at the link provided below.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
