Temp - Senior Prompt/AI Engineer – Clinical Study Medical Writing

Neurocrine Biosciences • San Diego, CA

31d

About The Position

We are seeking a Senior Prompt Engineer / AI Engineer to design, build, and deploy production-grade LLM systems that support clinical study medical writing workflows. This is a hands-on technical role focused on developing reliable, traceable, and regulation-aware AI solutions for drafting and quality control of Clinical Study Reports (CSRs), protocols, Investigator Brochures (IBs), safety narratives, and regulatory submissions. You will architect and implement structured prompt systems, retrieval-augmented generation (RAG) pipelines, and validation layers. Example tools include ChatGPT and custom GPTs (OpenAI); AWS services such as Amazon Bedrock (including Bedrock Agents/AgentCore) and AWS low-code workflow services; automation platforms such as n8n; orchestration frameworks like LangChain, LlamaIndex, and AutoGen; and data platforms such as Databricks for clinical data processing and integration.

Requirements

• Deep understanding of LLMs and advanced structured prompting techniques
• Demonstrated experience building and deploying LLM-powered systems in production
• Strong Python and backend engineering skills
• Experience designing validation frameworks for high-risk AI applications
• Ability to work in regulated or compliance-sensitive environments
• Strong analytical and technical problem-solving skills

Nice To Haves

• Clinical study medical writing experience (CSR, protocol, IB, regulatory submissions)
• Experience integrating structured clinical/statistical outputs (SDTM, ADaM, TLFs) into AI workflows
• Experience building RAG systems over regulated document corpora
• Familiarity with AI validation practices in GxP or similar environments

Responsibilities

• Design and implement section-aware prompt templates for efficacy, safety, methodology, and statistical interpretation
• Build deterministic multi-step workflows separating data extraction, validation, and narrative generation
• Develop and optimize RAG pipelines grounded in validated clinical artifacts (protocols, SAPs, TLFs, SDTM/ADaM)
• Implement traceability mechanisms linking generated content to source tables, listings, and figures
• Build automated guardrails and numerical consistency checks to prevent fabrication and cross-section discrepancies
• Develop evaluation and regression testing frameworks across model and prompt versions
• Deploy secure, scalable LLM services with logging, monitoring, and version control
• Work directly with medical writers, clinicians, and biostatisticians to translate drafting requirements into robust AI workflows

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed