About the RoleWe are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.
This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.
Key Responsibilities- Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
- Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
- Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
- Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
- Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
- Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
- Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.
Qualifications- Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
- Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
- Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
- Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
- Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).
Preferred- Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
- Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
- Understanding of privacy, security, and regulatory considerations in healthcare AI.
CompensationWe offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.
