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
