Lead Platform Engineer

BioLM is building an AI platform for molecular discovery, enabling researchers to design and analyze biological sequences using state-of-the-art language models. We are seeking a Lead Platform Engineer to own the architecture, development, and evolution of our core product platform. You'll work directly with the founding team to make high-leverage technical decisions - and be accountable for the reliability, scalability, and quality of what we ship. Responsibilities Ship products and features with startup-caliber velocity and a high bar for quality Lead the development of agentic workflows for molecular design and discovery Build and extend platform UI features that enable researchers to create, manage, and deploy fine-tuned protein and DNA models Integrate our Console, Builder, and Solutions apps into a seamless full-stack experience for molecular development Build API integrations with sequence and assay ordering providers, including internal data modeling and full-stack UI development Experience 5+ years of full-stack engineering experience, with a track record of shipping production systems end-to-end, from infrastructure to user-facing interface Led technical projects - scoped work, delegated effectively, and delivered on time Designed and operated cloud infrastructure at scale Built and maintained complex third-party integrations or API-driven systems Brought product instincts and UI sensibility to ambiguous, early-stage problems Required Qualifications Deep proficiency in Python and React/Node.js Strong command of cloud infrastructure (AWS or equivalent), CI/CD, and Docker Solid understanding of relational data modeling and API design patterns Experience with REST, WebSockets, and modern integration patterns including agentic/MCP-based systems A good eye for UI design and the product thinking to match Preferred Qualifications Experience building tooling for scientific, research, or ML/AI-adjacent workflows Familiarity with interactive data visualization (D3.js, Plotly, Vega-Lite) Experience integrating or deploying large-scale ML model APIs or agentic AI systems Background or genuine interest in biology, bioinformatics, or computational life sciences Originally posted on Himalayas