Software Engineer – Agentic Data Pipelines
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Job Description
Software engineer building agentic LLM systems for biomedical data acquisition, curation, and quality control. Supporting Iambic Therapeutics’ AI-driven drug discovery platform and Enchant model training.
Responsibilities:
- Design, build, and maintain agentic systems that convert biomedical data-source pointers into reviewed, versioned datasets
- Develop LLM-based pipelines for data cleaning, normalization, and formatting across molecular, genomic, clinical, and literature data
- Implement automated quality-control workflows to detect anomalies, flag inconsistencies, and enforce data standards
- Evaluate and iterate on agent architectures, prompting strategies, tool definitions, validation loops, and evaluation harnesses
- Collaborate with ML scientists on the Enchant team to translate data requirements into scalable acquisition and processing systems
- Monitor and maintain distributed data pipelines in production, diagnose failures, and improve robustness
- Document data provenance, processing decisions, and quality metrics for reproducibility and auditing
- Operate agents safely using sandboxed execution, least-privilege credentials, restricted network access, and audit logs
- Raise potential security risks to the team
- Contribute to a longer-term natural-language orchestrator for drug discovery inference, fine-tuning, virtual screens, and dataset analysis
Requirements:
- Master’s degree in a computational STEM field, or a Bachelor's with 2+ years of industry experience
- Strong Python engineering skills and experience building and maintaining production-quality software
- Hands-on experience with LLM APIs such as Claude and GPT
- Experience with agentic patterns including tool use, orchestration, and multi-step reasoning
- Familiarity with biomedical or chemical data sources and formats such as PDB, UniProt, ChEMBL, SDF/MOL, and FASTA
- Data engineering fundamentals including ETL design, data validation, and structured and unstructured data at scale
- Hands-on experience with Python testing frameworks such as pytest fixtures and parametrization
- Experience with agent orchestration frameworks and evaluation harnesses for LLM-generated code
- Familiarity with cloud infrastructure and workflow orchestration such as AWS, Docker, and 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 including sandboxing, scoped credentials, and prompt injection
- Authorized to work in the United States; visa sponsorship status addressed in application
Benefits:
- Company-paid healthcare
- Flexible spending accounts
- Voluntary life insurance
- 401K matching
- Uncapped vacation
- Onsite gym
- Dining facilities
- Brand-new state-of-the-art facility
- Easy access to great places to live and play
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