Job Title: Prompt Engineer / LLM Context Engineer
Location: London - 3 days onsite
Employment Type:Full-Time (Permanent)


Role OverviewWe are seeking a hands-on Prompt Engineer / LLM Context Engineer to design, build, and iteratively refine prompts, instruction frameworks, and context architectures that govern how large language models behave within enterprise AI applications.
This is a technical engineering role — not creative writing — focused on delivering consistent, accurate, and auditable outputs from LLM systems operating in a regulated life sciences environment.
The successful candidate will work at the intersection of AI engineering, retrieval systems, and domain collaboration, ensuring model outputs are reliable, measurable, and production-ready.
Key ResponsibilitiesPrompt & Instruction Engineering
*Design system prompts, structured instructions, and few-shot examples for production LLM use cases
*Iteratively refine prompts to resolve failures, edge cases, and domain-specific gaps
*Optimize prompt structure for consistency, determinism, and accuracy
Context Engineering & RAG
*Design and manage context pipelines for LLM applications
*Select, rank, and format retrieved content from knowledge bases and document stores
*Work closely with Retrieval-Augmented Generation (RAG) architectures to ground outputs in verified data
*Minimize hallucinations through strong context design
Evaluation Frameworks (Evals)
*Build and maintain systematic evaluation frameworks to measure prompt performance
*Define metrics for accuracy, consistency, and relevance
*Run regression testing and continuous prompt improvement cycles
*Use data-driven insights to guide prompt iteration (40–50% of role focus)
Cross-Functional Collaboration
*Partner with ML engineers, data scientists, and scientific SMEs
*Translate complex life sciences requirements into precise model instructions
*Support integration of LLM capabilities into production workflows
Prompt Governance & Compliance
*Maintain version control and documentation of prompt assets
*Ensure traceability suitable for regulated pharma environments
*Support audit readiness and reproducibility standards
Essential Skills & Experience*Proven hands-on experience engineering prompts for production LLM applications
*Strong understanding of:
*LLM behaviour and instruction following
*Context windows and tokenisation
*Hallucination mitigation techniques
*Practical experience with RAG (Retrieval-Augmented Generation) architectures
*Solid Python skills for scripting, testing, and automation
*Experience building or working with evaluation frameworks ("evals")
*Systematic, metric-driven approach to prompt iteration
*Strong stakeholder communication skills
Highly Desirable*Experience in life sciences, pharma, or regulated environments
*Familiarity with vector databases and retrieval pipelines
*Experience working with ML/AI engineering teams in production settings
*Understanding of governance requirements in regulated industries