Agentic AI Engineer - Autonomous Biological Discovery Systems

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

• 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