Senior Principal Research Software Engineer · AI/ML Platforms for Scientific Discovery
I build production-grade AI systems at the intersection of biology, genomics, healthcare, and large-scale computation. After 15+ years architecting data platforms, ecosystems and ML workflows at Genentech/Roche, the Wellcome Trust Sanger Institute, UK and the Max Planck Institute, Germany, I'm now focused on the next generation of AI-driven platforms for drug discovery and precision medicine.
AI-Enabled Scientific Workflows Multi-agent LLM systems for laboratory automation, LIMS integration, clinical trial site selection, large scale genomic workflows, and scientific data integration. Built production systems at Genentech that replaced weeks of manual analyst work with automated, auditable workflows — with human-in-the-loop review, parameter tracking and data provenance + lineage.
Large-Scale Distributed Processing Designed and operated genomic data pipelines scaling to 60,000+ parallel EC2 instances. Built FireDB and Sunrise — internal self-serve analysis platforms serving 500+ scientists and research staffacross Genentech's research organization — handling petabyte-scale genomic and clinical data.
| Domain | Tools |
|---|---|
| Languages | Python, Perl, SQL, Bash, Java, Go |
| ML / AI | LangChain, multi-agent frameworks (picoAgents), LLM APIs (Anthropic, OpenAI) |
| Cloud & Infra | AWS (EC2, S3, Batch, Lambda et al.), IaC, CI/CD, Docker |
| Data | PostgreSQL, MySQL |
- Genentech / Roche — Acting Director, Research Software Engineering. Built AI-supported workflows for genomics at scale. Scaled distributed compute to 60K+ parallel AWS EC2 nodes, including GPU.
- EMBL · Sanger Institute · Max Planck Institute — Early-career bioinformatics engineering across genome analysis, variant pipelines, and scientific data infrastructure.
I'm particularly drawn to problems where rigorous engineering meets scientific ambiguity — where the data is messy, the domain is deep, and getting it right actually matters for patients.
Exploring multi-agent system architectures and LLM integration patterns for scientific discovery. Currently deepening expertise in computational approaches to drug discovery, with a focus on production-grade AI deployment in regulated research environments.
Open to senior engineering roles building AI platforms at the frontier of computational drug discovery and healthcare.
📍 San Francisco Bay Area, CA · LinkedIn · Available for senior platform / ML engineering roles