Agentic Analytics Engineer

We are seeking an Agentic Analytics Engineer to join a growing team focused on building the next generation of AI-powered solutions supporting scientific research and drug development. This role is centered around leveraging Large Language Models (LLMs), agentic AI, and workflow automation to help scientists and business teams access, analyze, and interact with complex data more efficiently. The ideal candidate will have hands-on experience building AI agents, autonomous workflows, and enterprise AI solutions that deliver measurable business impact.

Day-to-Day Responsibilities:

• Design, build, and deploy agentic AI solutions that automate complex scientific and business workflows.
• Develop and orchestrate AI agents using frameworks such as LangChain, LangGraph, CrewAI, or similar technologies.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines that enable AI systems to access and reason over enterprise knowledge.
• Integrate Large Language Models with internal tools, databases, APIs, and enterprise platforms.
• Partner closely with scientists and business stakeholders to translate research and operational needs into scalable AI-driven solutions.
• Develop and maintain integrations with structured and unstructured data sources, including Snowflake and other enterprise systems.
• Evaluate, troubleshoot, and improve AI agent performance, reliability, and reasoning capabilities.
• Collaborate with cross-functional engineering teams to deliver enterprise AI initiatives.

• Strong software engineering experience with advanced proficiency in Python.
• Hands-on experience building AI-powered applications, autonomous agents, or workflow automation solutions.
• Experience working with Large Language Models (LLMs) and modern Generative AI technologies.
• Experience with agent orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar tools.
• Experience building or supporting RAG architectures and working with vector databases.
• Strong SQL skills and experience working with modern data platforms such as Snowflake.
• Experience integrating applications with APIs, enterprise systems, and external tools.
• Strong communication skills with the ability to partner effectively with technical and non-technical stakeholders., * Experience within biotechnology, pharmaceutical, healthcare, or life sciences organizations.
• Experience partnering directly with scientists, researchers, or other domain experts.
• Familiarity with Model Context Protocol (MCP), tool calling, and autonomous workflow designs.
• Experience developing enterprise AI solutions in production environments.
• Portfolio, GitHub repository, or examples of AI projects demonstrating hands-on agentic AI experience., * Bachelor's, Master's, or PhD in Computer Science, Data Science, Software Engineering, or a related technical field preferred.
• Equivalent hands-on experience building and deploying AI solutions will also be considered.