Software Developer; KBase

Berkeley Lab’s (LBNL) Environmental Genomics and Systems Biology (EGSB) Division is looking for a Software Developer to join the US Department of Energy’s (DOE) Systems Biology Knowledgebase (KBase) team!

KBase integrates diverse biological datasets, computational models, and analytical tools into a unified, extensible platform that enables researchers to generate, test, and refine hypotheses about biological systems. KBase supports large-scale, collaborative, and reproducible science across microbial ecology, functional genomics, and systems biology.

In this exciting role, you will design, develop, and maintain software infrastructure that enables AI-driven scientific workflows, including intelligent agents that interact with the KBase Data Lakehouse and associated knowledge resources. You will play a key role in building agentic systems, data services, and knowledge representations that allow AI tools to reason over harmonized, ontologically labeled biological data.

This position emphasizes the development of AI agents and co-scientist tools, integration with large-scale data lakehouse infrastructure, construction of knowledge graphs, and close collaboration with domain scientists. You will have the opportunity to contribute directly to scientific outputs, including publications, and help shape the next-generation AI-assisted discovery workflows within KBase.

This position has an anticipated start date of March 2, 2026.

We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

We invest in our employees by offering a total rewards package you can count on:

• Exceptional health and retirement benefits, including pension or 401K-style plans.
• A culture where you’ll belong - we are invested in our teams!
• Enjoy a Winter Holiday shutdown every year.
• Parental bonding leave (for both mothers and fathers).

• Lead the design and development of AI agents integrated with the KBase Narrative Interface, KBase Apps, and data services.
• Develop agent-based tools using Python, Lang Chain, Lang Graph, CrewAI, and modern large language models (e.g., OpenAI GPT-5.2, Claude Opus 4.5, Deep Seek, Kimi).
• Implement AI agents that interact with the KBase Datastore, a Delta Lake-based lakehouse built on PySpark.
• Design and maintain agent state management systems, prompt strategies, and benchmarking tools to ensure reliability and performance.
• Write robust, efficient, and well-tested code to support agent orchestration and pipeline integration.
• Collaborate with the AI/ML team to advance foundational models and tools for microbial genomics research.
• Contribute to front-end and back-end integration as needed to expose AI agent capabilities to end users.
• Develop, test, and maintain documentation and software artifacts in compliance with team standards and quality assurance procedures.
• Provide technical guidance and mentorship in AI tool design and system integration.

• A Bachelor’s Degree (or equivalent knowledge/training) in Computer Science, Engineering, Computational Biology, or a related field and a minimum of 5 years of relevant work experience in AI agent frameworks, data engineering, and software development in service of scientific research or an equivalent combination of education and experience.
• Experience designing and implementing intelligent agents for scientific or technical workflows.
• Demonstrated proficiency in Python and AI agent frameworks (Lang Chain, Lang Graph, and CrewAI).
• Experience working with large language models (LLMs) and prompt engineering across multiple providers.
• Skilled in PySpark and data engineering using lakehouse architectures (Delta Lake).
• Familiarity with machine learning libraries (PyTorch, Tensor Flow, Scikit-learn).
• Knowledge of open-source collaboration, Git Hub workflows, and Agile practices.
• Strong grasp of AI agent state management, evaluation, and benchmarking.
• Familiarity with deploying data/compute-intensive workflows on HPC or cloud research infrastructure.
• Excellent oral and…