BioMedical AI Research Engineer

<div class="content-intro"><p><strong>About Xaira Therapeutics</strong></p> <p>Xaira is an innovative biotech startup focused on leveraging AI to transform drug discovery and development. The company is leading the development of generative AI models to design protein and antibody therapeutics, enabling the creation of medicines against historically hard-to-drug molecular targets. It is also developing foundation models for biology and disease to enable better target elucidation and patient stratification. Collectively, these technologies aim to continually enable the identification of novel therapies and to improve success in drug development. Xaira is headquartered in the San Francisco Bay Area, Seattle, and London.</p></div><p><strong>About the Role</strong><strong><br></strong>We 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.</p> <p>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.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li>Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.</li> <li>Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.</li> <li>Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.</li> <li>Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.</li> <li>Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.</li> <li>Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.</li> <li>Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.</li> </ul> <p><strong>Qualifications</strong></p> <ul> <li>Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.</li> <li>Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.</li> <li>Experience building agent-b