Staff Engineer, Research Informatics and AI

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 Staff 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.

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 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.

Preferred Qualifications:

• 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.
• Experience 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.
• Experience 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.

Pay Range

$191,425 - $219,240

The annual base salary range listed above represents the lowest and highest amounts we reasonably and in good faith expect to pay for this position at the time of posting. An individual’s starting base salary within this range will be based on relevant experience, job-related skills, and education relevant to the role. In addition to base salary, this position offers bonus and equity opportunities, as well as benefits.