12 of 12 Permanent Prompt Engineering Jobs in the City of London

SOTA Evaluation Pipelines: Build a robust, high-scale evaluation framework to benchmark our proprietary models and steer the direction of our R&D. Advanced Prompt Engineering: Research and implement cutting-edge prompting methods to maximize model efficacy. Full-Stack Impact: While focused on AI, you’ll work across … shipping AI solutions. Production Experience: A history of shipping algorithms and/or evaluation pipelines into live environments. LLM Mastery: Practical experience with prompt engineering and modern LLM architectures. Technical Versatility: Familiarity with the full stack (Postgres, TypeScript, React). Clear Communication: Ability to articulate complex technical decisions ...

ALTEN , an engineering and technology consultancy, We are a leading Engineering and IT consultancy operating across 30 countries, making waves in all sectors: Aeronautics, Space, Defence, Security and Naval, Automotive, Rail and mobility, Energy and environment, Life Sciences and health, Industrial Equipment and electronics, Telecoms, Banking, Finance & Insurance … Deep Learning , Natural Language Processing , Computer Vision , Generative AI , Reinforcement Learning , LLMs (e.g., GPT, Claude, Mistral, LLaMA, DeepSeek, etc.). Agent-based architectures , RAG , prompt engineering , chatbots , classification , summarization , speech-to-text , image understanding. Cloud platforms (AWS, Azure, GCP). ML Ops tools and deployment workflows. AI-assisted ...

powered solutions for tracing, evaluation, and production monitoring. Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails. Design feature engineering approaches and contribute to feature store development. Support production models through monitoring, performance analysis, and continuous improvement. Apply responsible AI practices, including model explainability … with governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). Understanding of model evaluation, validation, and production monitoring. Strong problem-solving ...

proficiency in Python and experience with PyTorch or TensorFlow . Practical experience with LangChain, LangGraph, AutoGen , or similar LLM/agent frameworks. Skilled in prompt engineering , integrating foundation model APIs, and LLM fine-tuning techniques. Expertise in building RAG systems , vector databases (e.g., Pinecone, Weaviate), and embedding pipelines. ...

features like RAG, document analysis, and automated workflows. Full-Stack Lite: Use Python and Streamlit to create clean, interactive, and client-ready user interfaces. Prompt Engineering: Design and optimize complex system prompts to ensure reliable model outputs for business use cases. Requirements: The "Cursor" User ...

materials Work with leadership to define our long-term AI roadmap Lay the foundation for adaptive learning, personalised coaching, and automated formative assessment Set engineering standards, model safety guidelines, and data governance frameworks Help scale the AI stack into a proprietary academic engine used by thousands of learners This … technical core of an entire institution. What we’re looking for Essential Experience with Azure OpenAI, OpenAI, LangChain, or similar frameworks Strong Python engineering skills Practical experience building RAG systems, embeddings, vector stores Comfort with cloud architecture (Azure preferred) Ability to move fast, prototype, and ship Experience building MVPs ...

Python , and familiar with front-end frameworks like React. Skilled in SQL , data warehousing ( BigQuery ), and data visualisation. Knowledgeable about AI integration , agent frameworks, prompt engineering, and observability tools. Familiar with automation, ETL/ELT, and modern software engineering practices. ...

Large-Scale AI Deployments – Has played a key role in production-ready AI applications Expertise in LLMs – Skilled in fine-tuning, training, and prompt engineering AI Model Optimization – Strong knowledge of cost management, evaluation, and modification Solution Architecture – Can design and build AI solutions from scratch Client Engagement ...

data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based services Great knowledge of NLP algorithms: tokenisation, embeddings, attention, language modelling ...

Desirable Skills Experience using R and NLP or deep learning techniques (e.g., TF-IDF, word embeddings, CNNs, RNNs). Familiarity with generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, or Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience ...

Company: Salyant Ltd Location: United Kingdom (Remote) Engagement Type: Independent Contractor | Commission-Only Salyant Ltd delivers production-grade AI engineering and automation services across IT and SaaS environments for UK businesses. We design, build, integrate, and deploy AI systems that operate in live production environments — not pilots, demos … Development Officer (BDO) to own UK market sales, responsible for sourcing, qualifying, and closing opportunities for implementation-ready AI services delivered by our AI engineering team. Services You Will Sell (Strict Delivery Scope): You will sell only the following services: Custom AI implementations aligned to specific business use cases ...

lead the design and productionisation of Generative AI and Large Language Model (LLM) applications. This role sits at the heart of an AI-focused engineering team, delivering scalable, production-grade systems using GCP and Google's AI ecosystem . You'll be a senior, hands-on engineer owning complex … including fine-tuning, vector search, and low-latency inference. Build end-to-end LLM applications , leveraging RAG (Retrieval-Augmented Generation) , agentic workflows, and prompt engineering. Implement robust evaluation frameworks to monitor LLM quality, hallucinations, token usage, and content safety. Develop and deploy autonomous or semi-autonomous agents using modern ...