Agentic AI Engineer - Autonomous Biological Discovery Systems
Is this the role you are looking for If so read on for more details, and make sure to apply today.
Position Overview
We are seeking a visionary Agentic AI Engineer to architect and implement autonomous AI systems that will revolutionize transcriptome analysis and precision medicine. This role goes beyond traditional AI development to create systems that can independently reason, plan, and execute complex biological research workflows. You will build the cognitive architecture that transforms our AI from a tool into an intelligent collaborator capable of formulating hypotheses, designing experiments, and discovering novel biological insights with minimal human intervention.
Key Responsibilities
Agentic System Architecture
Design and implement multi-agent systems for autonomous transcriptome analysis
Develop agentic workflows that can dynamically select analysis methods based on data characteristics
Create autonomous decision-making frameworks for quality control and sample processing
Build self-improving systems that learn from experimental outcomes
Implement feedback loops enabling continuous workflow optimization
Reasoning & Planning Systems
Develop causal reasoning engines for biological hypothesis generation
Implement Monte Carlo Tree Search and similar algorithms for experimental planning
Create counterfactual reasoning capabilities for testing gene function hypotheses
Build temporal reasoning systems for understanding gene expression dynamics
Design explanation generation systems for autonomous decision documentation
Autonomous Workflow Development
Create agents that can autonomously navigate from raw sequencing data to biological insights
Implement dynamic pipeline selection based on data quality and research objectives
Develop agents capable of identifying and resolving batch effects without human intervention
Build systems that can autonomously formulate follow-up experiments
Design collaborative multi-agent architectures for complex biological problems
Knowledge Integration & Learning
Implement continuous learning systems that update from new scientific literature
Create knowledge graphs that agents can query and update autonomously
Develop mechanisms for resolving contradictions between different data sources
Build systems for autonomous validation of biological findings
Design meta-learning frameworks for improving agent performance over time
Required Qualifications
Technical Expertise
MS/PhD in Computer Science, AI, Robotics, or related field
3+ years of experience in autonomous systems or multi-agent AI
Expert proficiency in Python with focus on agent frameworks (LangChain, AutoGPT, AgentGPT)
Strong background in reinforcement learning and planning algorithms
Experience with causal inference and probabilistic reasoning
Proven track record in building production autonomous systems
AI/ML Skills
Deep understanding of agentic AI architectures and design patterns
Experience with LLM orchestration and tool use
Knowledge of symbolic reasoning and knowledge representation
Familiarity with neurosymbolic AI approaches
Experience with distributed agent systems
Systems Thinking
Ability to design complex, self-organizing systems
Experience with workflow orchestration and automation
Understanding of feedback control systems
Knowledge of system reliability and fault tolerance
Preferred Qualifications
Experience with biological or medical AI applications
Knowledge of bioinformatics workflows and pipelines
Familiarity with laboratory automation systems
Understanding of clinical trial design and execution
Publications in autonomous AI or multi-agent systems
Experience with robotic process automation
Background in cognitive architectures
Key Performance Metrics
Deploy autonomous agents achieving 90%+ accuracy in analysis decisions
Reduce human intervention in standard workflows by 80%
Enable autonomous hypothesis generation with 70%+ validation rate
Achieve 99.9% reliability in production autonomous systems
Successfully orchestrate 100+ concurrent agent workflows
Integration Responsibilities
Cross-Team Collaboration
Partner with
LLM Engineers
to integrate reasoning capabilities into autonomous agents
Work with
Software Engineers
to build scalable agent execution platforms
Collaborate with
Bioinformaticians
to encode domain expertise into agent behaviors
Interface with
Clinical teams
to ensure agent decisions meet regulatory standards
Platform Integration
Design APIs for human-agent collaboration interfaces
Create monitoring dashboards for autonomous system oversight
Implement audit trails for all autonomous decisions
Build simulation environments for agent testing and validation
What We Offer
Opportunity to pioneer autonomous AI in life sciences
Work on systems with direct impact on drug discovery and patient care
Collaboration with world-class AI researchers and biologists
Competitive salary ($190,000 - $300,000) based on experience
Comprehensive benefits package with equity participation
Dedicated budget for AI research and experimentation
Conference attendance and publication support
Remote-first culture with quarterly team gatherings
The Transformative Opportunity
This role offers the chance to build AI systems that function as true scientific collaborators, not just tools. Your work will enable:
Autonomous discovery of novel therapeutic targets
Self-directed exploration of biological mechanisms
Intelligent systems that can reason about causality in biology
AI agents that can design and interpret their own experiments
Application Requirements
Please submit:
Resume/CV highlighting autonomous systems projects
Portfolio demonstrating multi-agent or autonomous AI work
Technical writing sample or system architecture document
Brief proposal for an autonomous biological discovery system
Optional: Demo of an autonomous agent you've built
Contact: