Principal Engineer, Data Infrastructure and Informatics

What if… you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?

FL94 Inc., is a privately held, early-stage biotechnology company pioneering Protein Editing. At FL94 we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of novel chemistry modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with machine learning to enable generative design of protein editing chemistries. FL94 is backed by Flagship Pioneering, bringing the courage, vision, and resources to guide FL94 from platform validation to patient impact. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us! 

Position Summary: 

We are seeking a highly skilled and innovative Principal Engineer, Data Infrastructure and Informatics. This position offers the opportunity to design, integrate, and optimize the data infrastructure critical to driving our AI/ML drug-discovery platform. You will be at the forefront of shaping our data systems to support AI/ML and drug development capabilities, ensuring robust and scalable solutions for the collection, management, and analysis of large-scale multi-omics data. 

Responsibilities: 

• Multi-Omics Data Infrastructure Design & Optimization: Architect and deploy of data solutions that integrate experimental data with computational tools, ensuring high availability, scalability, and security. Experience with mass spectrometry and/or NGS data sets is highly desired.
• Integration & Automation: Automate workflows across proteomics research environments, including high-throughput proteomic assays, mass spectrometry data processing, and bioinformatics tools. Integrate these systems with LIMS (Laboratory Information Management Systems) for seamless data capture.
• Collaboration & Support: Work closely with machine learning and data scientists, bioinformaticians, and pre-clinical teams to translate business needs and scientific objectives into data infrastructure solutions. Provide technical support and expert advice.
• Data Governance & Quality: Ensure rigorous standards for data integrity, discoverability, and consistency. Implement best practices for data capture, storage, and sharing across both manual and automated workflows.
• Data Strategy Leadership: Develop and implement a comprehensive data strategy to support the rapid scaling of AI/ML research in proteomics, enabling empirical data collection at scale.
• Technical Leadership: Design and deploy cloud-based infrastructure for biological and proteomics data processing, storage, and analysis. Implement DevOps and CI/CD pipelines to ensure continuous improvement of data systems.
• Stakeholder Communication: Regularly present to senior leadership and external stakeholders, providing updates on progress, challenges, and opportunities related to data infrastructure initiatives.

Qualifications: 

• 10+ years of experience in R&D data infrastructure, informatics, or related fields. Experience in proteomics, bioinformatics, ML Ops, or related areas is highly desirable.
• BS degree in Computer Science, Data Engineering, Computational Biology, Proteomics, or a related field. Advanced degree is a plus.
• Proven track record in designing and implementing large-scale data systems in a proteomics, biotech, or life sciences environment.
• Expertise in cloud infrastructure (e.g., AWS, Azure, GCP) and services such as EC2, S3, Lambda, and kubernetes.
• Experience with database/data warehouse systems (g. RDS, Postgres, Redshift, BigQuery, Snowflake)
• Experience with data pipeline architecture (e.g., Flyte, Apache Airflow, Nextflow) and software integration (e.g., APIs, schedulers, workflow orchestration).
• Strong knowledge of data management systems (e.g., LIMS, Dotmatics, CORE LIMS) and related tools.
• Deep experience with the Python development stack.
• Experience in DevOps and automation tools (e.g., Jenkins, Terraform, Ansible) is a plus.
• Strong communication and presentation skills, with the ability to interact