Agentic Analytics Engineer

As an Agentic Analytics Engineer in Synthetic Molecule Pharmaceutical Sciences

(SMPS) in Genentech, you will be responsible for integrating scientific and business

data from multiple sources to generate agentic analytics product. You will be connecting

Large Language Models (LLMs) to enterprise tools, databases, and APIs to enable

conversational data analytics, and contributing to the development of life-saving, * Agent Orchestration: Use frameworks like LangChain, CrewAI, or LangGraph to build specialized agents

• Tool Integration: Implement the Model Context Protocol (MCP) to connect agents to internal systems like Microsoft Suite, Slack, or SQL databases.
• Workflow Mapping: Translate complex business processes (like "genotoxic impurity profile of a therapeutic molecule") into a series of logical steps an AI can follow.
• RAG Pipeline Maintenance: Build and optimize Retrieval-Augmented
• Generation (RAG) systems using vector databases (e.g., Pinecone, Weaviate) to give agents access to enterprise knowledge and data.
• Evaluation & Debugging: Use "LLM-as-a-Judge" frameworks to test agent reliability, find where reasoning loops fail, and implement "Human-in-the-Loop" (HITL) approval gates.

• Language: Python and SQL (advanced)
• Data Stack: Modern data warehouses such as Snowflake
• Frameworks: LangChain and LangGraph
• Orchestration: Mastery of reasoning loops (ReAct, Chain-of-Thought)
• Protocols: Model Context Protocol and RESTful API integration

Nice to Haves:

• Experience in web application development
• Basic understanding of chemistry and drug development and relevant experience in biotech or pharmaceutical companies

Education/Certification(s)/License(s):

• Education: B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field, with 1+ years of professional work experience
• Portfolio: Evidence of building at least one autonomous system (e.g., an agent that can successfully scrape a site, summarize findings, and email a report without human intervention).