Laboratory Planning Engineer

BioArk Genome Engineering Operating System (BioArk GEOS) 

Project Vision 

• Current CRISPR software mainly focuses on guide RNA design or individual bioinformatics 

tasks, while successful genome engineering requires engineering strategy selection, feasibility 

analysis, laboratory planning, sequencing validation, quality control, and continuous 

optimization. 

• The BioArk AI CRISPR Engineering Platform is an AI Engineering System implementing a 

Design–Build–Test–Learn (DBTL) workflow. 

• Bioinformatics is treated as one component of a larger engineering ecosystem. 

• The platform leverages biomedical AI systems (e.g. Biomni) for biological reasoning while 

BioArk develops proprietary engineering intelligence, laboratory planning, sequencing 

interpretation and continuous learning.

Laboratory Planning & Workflow Generation Agent Engineers

Role Summary

You will build the AI Engineering Planning, Digital Twin & Workflow Generation Engine, responsible for transforming validated genome engineering strategies into optimized laboratory execution plans through AI-driven engineering simulation, workflow planning, protocol generation, and resource orchestration.

Key Responsibilities

• Develop AI Digital Twin models that simulate laboratory execution, predict engineering success, identify technical bottlenecks, and compare alternative execution strategies before experiments begin. 
• Design intelligent planning engines that automatically generate optimized laboratory workflows, SOPs, plasmid maps, PCR protocols, sequencing plans, and genome engineering execution packages. 
• Build AI scheduling and resource orchestration systems that optimize technician assignments, laboratory workflows, equipment utilization, inventory allocation, and project timelines. 
• Develop AI-driven quality planning and engineering control systems that establish QC checkpoints, validation gates, and automated workflow optimization throughout laboratory execution. 

Deliverables

AI Engineering Planning Reports, Digital Twin Simulation & Success Prediction Reports, Complete Laboratory Execution Packages, Automated SOPs & Workflow Plans, Quality Planning Reports, and structured Engineering Execution Packages.

Required Skills

Strong expertise in genome engineering workflows, laboratory automation, workflow engineering, AI prediction models, Digital Twin technologies, Python programming, and scientific workflow orchestration.