AI Prompting Engineer - Biological Reasoning Systems

We are seeking an innovative AI Prompting Engineer to optimize the interface between human expertise and artificial intelligence in our revolutionary transcriptome analysis platform. This role is critical in unlocking the full potential of our LLM and agentic AI systems by crafting sophisticated prompting strategies that enable complex biological reasoning. You will bridge the gap between cutting-edge AI capabilities and the nuanced requirements of genomic research, ensuring our AI systems produce accurate, explainable, and clinically relevant insights from differential expression gene (DEG) analyses. Key Responsibilities Advanced Prompting Strategy Development Design and optimize complex prompting architectures for biological reasoning tasks Develop chain-of-thought (CoT) prompts that guide LLMs through multi-step genomic analyses Create tree-of-thoughts (ToT) frameworks for exploring alternative biological hypotheses Implement ReAct prompting for dynamic agent-environment interactions in research workflows Build self-consistency prompting systems to reduce output variability from 30% to

Domain-Specific Prompt Engineering Craft specialized prompts for interpreting 20,000+ gene expression patterns Develop role-based prompting strategies simulating expert bioinformaticians and clinicians Create contextual prompting frameworks incorporating patient history and experimental conditions Design step-back prompting for identifying underlying biological mechanisms Implement structured output prompts for clinical report generation Prompt Optimization & Automation Build automated prompt engineering systems using LLMs to generate optimal prompts Develop prompt ensembling techniques for improved reliability Create prompt debiasing strategies for fair and accurate biological interpretations Implement prompt versioning and A/B testing frameworks Design prompt templates with dynamic variables for scalable deployment Quality Assurance & Validation Establish prompt evaluation metrics specific to biological accuracy Develop unit testing frameworks for prompt outputs Create calibration techniques for LLM confidence in biological predictions Implement prompt injection protection for clinical-grade security Build monitoring systems for prompt performance in production Required Qualifications Technical Expertise BS/MS in Computer Science, Computational Biology, Bioinformatics, or related field 2+ years of experience in prompt engineering or NLP applications Expert proficiency in Python with focus on LLM frameworks Deep understanding of prompt engineering techniques and best practices Experience with multiple LLM platforms (GPT-4, Claude, Gemma, etc.) Strong background in structured output generation (JSON, XML, CSV) Prompt Engineering Skills Mastery of advanced prompting techniques (zero-shot, few-shot, chain-of-thought) Experience with prompt optimization and automated evaluation Knowledge of sampling parameters (temperature, top-k, top-p) tuning Understanding of context window management and token optimization Proven ability to reduce LLM hallucinations through prompt design Domain Understanding Familiarity with biological terminology and genomics concepts Understanding of scientific reasoning and hypothesis testing Experience with technical documentation and report generation Knowledge of clinical communication requirements Preferred Qualifications Experience with biological or medical AI applications Background in RAG (Retrieval-Augmented Generation) systems Knowledge of causal reasoning and inference techniques Familiarity with regulatory requirements for clinical AI Publications or contributions to prompt engineering research Experience with multi-modal prompting (text + data) Understanding of differential expression analysis workflows Key Performance Metrics Achieve 95%+ biological accuracy in LLM-generated analyses Reduce prompt token usage by 40% while maintaining quality Enable 10x faster development of new analysis workflows Achieve

Successfully deploy 100+ production-ready prompt templates Maintain 99%+ consistency in structured output generation Integration Responsibilities Cross-Team Collaboration Partner with LLM Engineers to optimize prompts for specific models Support Agentic AI Engineers with prompts for autonomous decision-making Work with Software Engineers to implement prompt management systems Collaborate with Bioinformaticians to encode domain expertise in prompts Interface with Clinical teams to ensure outputs meet medical standards Platform Development Design prompt libraries for common biological analysis tasks Create prompt composition frameworks for complex workflows Build interactive prompt debugging and testing tools Develop documentation and training materials for prompt usage Implement prompt governance and quality control processes Technical Focus Areas Biological Reasoning Prompts Causal Analysis: "Given expression changes in genes X, Y, Z, identify potential causal relationships..." Pathway Integration: "Analyze how these DEGs interact within known signaling pathways..." Clinical Interpretation: "Translate these expression patterns into clinically actionable insights..." Hypothesis Generation: "Based on these findings, propose testable hypotheses for..." Prompt Architecture Patterns Hierarchical Prompting: Breaking complex analyses into manageable sub-tasks Iterative Refinement: Self-improving prompts based on output quality Context Injection: Dynamically incorporating experimental metadata Constraint Specification: Ensuring biologically valid outputs Explanation Chaining: Generating step-by-step reasoning traces What We Offer Pioneer the intersection of prompt engineering and precision medicine Work with state-of-the-art LLMs and biological datasets Shape how AI interprets and reasons about genomic data Comprehensive benefits package with equity participation $3,000 annual budget for AI conferences and training Access to cutting-edge AI models and computational resources Remote-first culture with flexible working arrangements The Unique Challenge This role offers the opportunity to: Transform how AI systems understand and reason about biology Create prompting strategies that enable autonomous scientific discovery Bridge the gap between AI capabilities and clinical requirements Develop novel prompting techniques for scientific applications Build the linguistic interface for the future of genomic medicine Career Growth Opportunities Lead prompt engineering initiatives across multiple biological domains Contribute to research publications on scientific prompt engineering Develop into AI/Biology translation specialist roles Progress to principal engineer or technical lead positions Shape company-wide AI interaction strategies