Staff Engineer, Research Informatics and AI
Superluminalrx · Boston, MA
About this role
**About Superluminal Medicines** Superluminal Medicines is a generative biology and chemistry company revolutionizing the speed and accuracy of how small molecule medicines are created. Our platform aims to create candidate-ready compounds with unprecedented speed using deep biology, computational and medicinal chemistry, machine learning, and proprietary big data infrastructure. We’re expanding our team of talented scientists who want to build the future of small molecule drug discovery through creativity and innovation. **About the Role** We’re seeking a **Staff Engineer** to design and build the software systems that power how experimental data moves through Superluminal Medicines. You’ll own critical systems at the intersection of software engineering, scientific data, and research operations—covering **compound registration, experimental data ingestion, scientific system integrations, and the infrastructure connecting wet lab workflows to our broader data platform**. This is a **high-ownership engineering role**. You’ll design production systems, make architectural decisions, write high-quality software, and work directly with scientists to solve complex technical problems. **Key Responsibilities** - Design, build, and operate production software systems supporting scientific data and wet lab workflows. - Own the architecture and implementation of systems for compound registration, experimental data ingestion, validation, transformation, and publishing. - Build reliable integrations across internal applications, APIs, cloud services, databases, and third-party scientific platforms. - Develop backend services, data pipelines, and internal applications used directly by scientists and research teams. - Design systems that are observable, testable, resilient, and maintainable as scientific workflows and data volumes scale. - Work directly with scientists to understand operational problems, identify root causes, and translate ambiguous workflows into clear technical solutions. - Improve data quality and system reliability through validation frameworks, automated testing, monitoring, and well-defined interfaces. - Establish strong engineering practices around code quality, CI/CD, deployment, documentation, and operational ownership. **Minimum Qualifications** - Bachelor’s degree in Software Engineering, Computer Science, Information Technology, or a related field; or equivalent professional experience. - 5+ years of professional software engineering experience building and operating production systems. - 3+ years of **Python** experience designing maintainable and well-tested software. - Experience building systems integrating data across APIs, databases, files, asynchronous processes, and third-party platforms. - Experience with containers and modern deployment patterns using **Docker** and **Kubernetes**. - Experience designing scalable software architecture and making technical design decisions. - Experience designing and consuming **REST APIs**. - Experience developing production systems on **Google Cloud Platform** and cloud-native architecture. - Experience leading SQL queries, designing relational data models, and developing production data pipelines/workflows. - Experience developing and operating production software using automated testing, CI/CD, monitoring/logging, and incident troubleshooting. **Preferred Qualifications** - 8+ years of professional software engineering experience building and operating production system
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