Research Informatics Software Engineer

• Integrate, extend, and support vendor Laboratory Information Management Systems (LIMS), Electronic Lab Notebooks (ELN), and analytical informatics platforms. Scope includes platforms such as Genedata, CDD Vault, Virscidian Analytical Studio, and similar systems-focusing on data models, workflows, APIs, sample/analytical data flows, and connections to instruments and enterprise systems.
• Design, implement, and maintain scalable data pipelines and APIs that make scientific data (samples, assays, analytical results, automation streams) FAIR, high-quality, and machine-actionable for both human scientists and AI agents. Leverage modern data platforms, warehouses/lakes, and orchestration tools.
• Build and operate cloud-native components (primarily AWS) using containers (Docker/Kubernetes), infrastructure patterns, CI/CD, and workflow orchestration to support lab informatics and AI workloads.
• Prototype and productionize agentic AI / GenAI solutions-LLM agents, RAG and GraphRAG systems, multi-agent workflows, and prompt-engineered / retrieval-augmented pipelines-that automate or augment laboratory informatics processes, data interpretation, and closed-loop experimentation.
• Collaborate with research scientists and cross-functional engineering teams to translate scientific needs into reliable software, data products, and AI capabilities; contribute to documentation, testing, and knowledge transfer.
• Apply software engineering best practices (agile / AI-agile delivery, testing, schema design, performance tuning) in a scientific computing context.
• Support continuous improvement of lab digital systems, including data quality, observability, and readiness for AI agents.

• Master’s degree in Computer Science (or a closely related field) with relevant coursework in cloud computing and the fundamentals of AI and ML.
• Demonstrated experience building data pipelines, feature engineering, or scientific data workflows (e.g., Spark/Databricks-style pipelines, data quality checks, performance tuning).
• Hands-on experience with cloud platforms (AWS), containers (Docker/Kubernetes), and modern data/backend tools (SQL, PostgreSQL, orchestration frameworks).
• Strong proficiency with AI coding assistants and coding agents (e.g., Cursor, Claude Code, GitHub Copilot, or similar tools).
• Familiarity with LLM concepts, RAG, retrieval, or multi-agent systems (coursework, projects, or professional exposure).
• Willingness and aptitude to rapidly learn commercial LIMS/ELN or analytical platforms (e.g., Genedata, CDD Vault, Virscidian Analytical Studio); prior exposure is a plus.
• Proficiency in Python and SQL; additional experience with C++/C, high-performance ML tooling, or scientific computing libraries is a plus.
• Strong collaboration skills and ability to work at the intersection of software engineering, data, and scientific applications.

Preferred Qualifications

• Practical, hands-on experience with LLM / agentic AI systems, including RAG, GraphRAG, multi-agent architectures, or production retrieval-augmented pipelines.
• Experience optimizing high-performance ML or scientific models (e.g., protein structure prediction, surrogate modeling, Bayesian optimization).
• Hands-on work with multi-agent systems, knowledge graphs (Neo4j), or agent frameworks/SDKs.
• Familiarity with Airflow or Prefect, PyTorch, and related ML/LLM tooling.
• Direct experience with commercial LIMS/ELN or analytical platforms such as Genedata, CDD Vault, Virscidian Analytical Studio, or similar-especially their data models, APIs, and integration points.
• Experience with CI/CD, testing, schema design, and production-grade software practices.
• Interest in applying agentic AI and robust data engineering to laboratory and drug-discovery workflows.

The salary range for this position is $120,000- $160,000 per year. The actual compensation offered will be based on factors such as relevant experience, education, and skills. In addition to base salary, we offer a comprehensive benefits package, including health insurance, paid time off and other benefits.