About Superluminal Medicines:
Superluminal Medicines is a generative biology and chemistry company revolutionizing the speed and accuracy of how small molecule medicines are created. The Company’s platform aims to create candidate-ready compounds with unprecedented speed using a combination of deep biology, computational and medicinal chemistry, machine learning, and proprietary big data infrastructure. We are expanding the team of talented scientists who seek to build the future of small molecule drug discovery with creativity and innovation.
About the Role:
We are seeking a Senior Software Engineer to design and build the software systems that power how experimental data moves through Superluminal Medicines.
You will own critical systems at the intersection of software engineering, scientific data, and research operations, including compound registration, experimental data ingestion, scientific system integrations, and the infrastructure that connects wet lab workflows to our broader data platform.
This is a high-ownership engineering role. You will be expected to design production systems, make architectural decisions, write high-quality software, and work directly with scientists to solve complex technical problems. The ideal candidate is a strong software engineer who is excited by difficult integration challenges, evolving requirements, and the opportunity to build foundational systems in a modern drug discovery organization.
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.
- 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 that integrate 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 or workflows.
- Experience developing and operating production software using automated testing, CI/CD pipelines, application monitoring, logging, and incident troubleshooting practices.
- 8+ years of professional software engineering experience building and operating production systems.
- Experience in biotechnology, pharmaceuticals, life sciences, or another technically complex scientific environment.
- Experience with LIMS, ELNs, compound registration systems, laboratory informatics, inventory platforms, or scientific instruments.
- Familiarity with drug discovery data, including compounds, assays, experimental results, and scientific metadata.
- Experience with BigQuery, dbt, Dagster, or similar modern data platforms and orchestration tools.
- Experience building internal tools or user-facing applications for technical users.
- Familiarity with scientific Python, cheminformatics, or bioinformatics workflows.
- Experience with infrastructure-as-code and cloud security best practices.
- Experience modernizing manual, fragmented, or vendor-dependent operational workflows.
Benefits:
Superluminal offers a comprehensive benefits package that fully covers employees’ annual deductibles and monthly premiums for medical, dental, and vision insurance. The package also includes a 401(k) match program, a Massachusetts transportation subsidy, equity, unlimited paid time off, and both disability and life insurance.
Equal Opportunity Statement:
Superluminal Medicines is an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status.
Skills Required
- Bachelor's degree in Software Engineering, Computer Science, Information Technology, or related field; or equivalent professional experience.
- 5+ years professional software engineering experience building and operating production systems.
- 3+ years Python experience designing maintainable and well-tested software.
- Experience building systems that integrate 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 writing SQL, designing relational data models, and developing production data pipelines or workflows.
- Experience developing and operating production software using automated testing, CI/CD pipelines, application monitoring, logging, and incident troubleshooting.
- 8+ years professional software engineering experience building and operating production systems.
- Experience in biotechnology, pharmaceuticals, life sciences, or another technically complex scientific environment.
- Experience with LIMS, ELNs, compound registration systems, laboratory informatics, inventory platforms, or scientific instruments.
- Familiarity with drug discovery data, including compounds, assays, experimental results, and scientific metadata.
- Experience with BigQuery, dbt, Dagster, or similar modern data platforms and orchestration tools.
- Experience building internal tools or user-facing applications for technical users.
- Familiarity with scientific Python, cheminformatics, or bioinformatics workflows.
- Experience with infrastructure-as-code and cloud security best practices.
- Experience modernizing manual, fragmented, or vendor-dependent operational workflows.
What We Do
Superluminal Medicines is a Boston-based generative biology and chemistry company developing a differentiated pipeline and revolutionizing the speed and accuracy of how medicine is created. Our platform creates candidate-ready compounds with unprecedented speed using a comprehensive combination of deep biology and chemistry expertise, machine learning, and proprietary big data infrastructure. The predict-design-test architecture accurately models protein shapes and designs highly selective compounds to target the precise structural change for therapeutic effect. Our discovery engine is powered by an industry-leading, pharmacokinetic and toxicology in silico prediction capability. With a lead program candidate expected in the near term, our proprietary pipeline validates our platform with initial programs focused on high-value GPCR targets. We’re pleased to be backed by a strong network of investors including RA Capital Management, Insight Partners, NVentures, Catalio Capital Management, Eli Lilly and Company, Gaingels, and Cooley LLP.
