Software Engineer — Agentic data pipelines
Indexed description
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.
Key Responsibilities
- 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
- 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)
- 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
MISSION & CORE VALUES
Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.
Pay And Benefits
We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.
Compensation Range: $110K - $162K
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search