Job Description
Job Title: Prompt Engineer / LLM Context Engineer
Location: London - 3 days onsite
Employment Type:Full-Time (Permanent)
Role Overview
We 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 Responsibilities
Prompt & 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