become a cyto
Make mom proud
become a cyto
Make mom proud
Careers
“For the very first time in human history, biology has the opportunity to be engineering, not science.”
- Jensen Huang, President and CEO, NVIDIA
In drug development, massive amounts of data are generated, but turning that data into clear, real-world decisions is still incredibly difficult. CytoReason exists to close this data-decision gap.
We are building an AI platform that transforms petabytes of biological information into decision-ready disease models. Our work brings together science and engineering, with direct impact on how new treatments reach patients.
As a Cyto, you’ll work on complex, real-world problems alongside talented teammates from different disciplines, all focused on the same goal: to empower scientists with tools to make faster, more accurate decisions that ultimately lead to better outcomes for patients.
Senior AI Engineer
About The Position
We are seeking a Senior AI Engineer to lead the design and development of agent-based AI systems that transform how computational biology work is done. This is a hands-on, high-ownership role focused on building production-grade AI tools that act as collaborators for scientists – automating workflows such as data interpretation, automatic annotation, and knowledge extraction.
You will operate at the intersection of cutting-edge AI (LLMs, agents) and real-world biological applications, helping define how agentic systems integrate into scientific research.
Responsibilities
- Lead the design and implementation of agentic AI systems for scientific workflows
- Build internal tools using LLMs, MCP, RAG pipelines, and multi-agent frameworks
- For example, develop systems for automatic annotation of biological data, literature understanding, and knowledge extraction
- Translate complex research workflows into AI-driven, semi-autonomous processes
- Take ownership from idea to production: prototype → deploy → iterate
- Work closely with computational biologists to identify and prioritize high-impact use cases
- Define best practices for agent reliability, evaluation, and performance in scientific contexts
- Contribute to the architecture of an AI-powered platform for biological discovery
Requirements
- 5+ years of experience in software engineering, applied AI, or ML systems
- Proven track record of owning and delivering production-grade systems
- Strong Python skills and solid software engineering fundamentals
- Hands-on experience with benchmarking, evaluation, and validation of LLM/agent-based systems, including defining success metrics, running experiments, and analyzing performance tradeoffs
- Hands-on experience with LLMs and agent frameworks (LangChain, OpenAI, Anthropic, or similar)
- Experience building tools/products used by internal users or customers
- Strong problem-solving skills and ability to operate in ambiguous, fast-moving environments
- Excellent communication skills and ability to work cross-functionally