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