Software Engineer — Agentic data pipelines

We are seeking a software engineer to join our team at Iambic Therapeutics, working on data acquisition and curation for Enchant , our multimodal transformer model trained at scale on a wide variety of biomedical data. In this role, you will design and build agentic systems that generate code to acquire, clean, format, quality-control, and generate auditable data reports for the large-scale datasets that power Enchant training. The model writes the code, the code runs the pipeline. You will work at the intersection of LLM-based automation and biomedical data engineering—developing AI agents that can navigate heterogeneous data sources, enforce quality standards, and operate reliably at scale. This role is ideal for candidates who combine strong software engineering instincts with scientific understanding of biomedical data, and who are excited about using LLMs as tools to solve practical data problems.

Design, build, and maintain agentic systems that turn a pointer to a biomedical data source (web page, S3 path, GitHub repository, a table in a paper) into a reviewed, versioned dataset. The agent's output is committed pipeline code and its test suite, so re-running it later reproduces the same dataset. Develop LLM-based pipelines for data cleaning, normalization, and formatting across diverse data modalities (e.g., molecular, genomic, clinical, literature) Implement automated quality-control workflows that detect anomalies, flag inconsistencies, and enforce data standards Evaluate and iterate on agent architectures, prompting strategies, tool definitions, validation loops, and evaluation harnesses that make agent-generated code trustworthy, improving reliability and throughput over time Collaborate with ML scientists on the Enchant team to understand data requirements and translate them into scalable acquisition and processing systems Monitor and maintain distributed data pipelines in production, diagnosing failures and improving robustness over time Document data provenance, processing decisions, and quality metrics to support reproducibility and auditing Operate the agents safely with sandboxed execution, least-privilege credentials, restricted network access, audit logs, and raising potential security risks to the team QUALIFICATIONS Master’s degree in a computational STEM field, or a Bachelor's with 2+ years of industry experience Strong Python engineering skills, including experience building and maintaining production-quality software Hands-on experience with LLM APIs (e.g., Claude, GPT) and agentic patterns such as tool use, orchestration, and multi-step reasoning Familiarity with biomedical or chemical data sources and formats (e.g., PDB, UniProt, ChEMBL, SDF/MOL, FASTA, or similar) Comfort with data engineering fundamentals: ETL design, data validation, and working with structured and unstructured data at scale Hands-on experience with Python testing frameworks (e.g., pytest fixtures, parametrization) PREFERRED QUALIFICATIONS Experience with agent orchestration frameworks, and with evaluation harnesses for LLM-generated code Familiarity with cloud infrastructure and workflow orchestration (e.g., AWS, Docker, Kubernetes) Knowledge of multimodal biomedical data—spanning small molecules, proteins, assays, images, ‘omics, and/or clinical records Experience with large-scale dataset construction or curation for ML model training Knowledge of agent security practices: sandboxing, scoped credentials, prompt injection Interest in a longer-term project: a natural language orchestrator that lets drug prosecution team members request inference, fine-tuning, virtual screens, and dataset analysis without writing code using our internal tools ABOUT IAMBIC THERAPEUTICS Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team