26 to 50 of 58 Prompt Engineering Jobs in London

Engineer - 350PD - Remote Required Technical Skills AWS & Generative AI Experience with AWS Bedrock including model selection, deployment, and prompt engineering Agentic workflow development, ideally using AWS AgentCore Multi-agent orchestration frameworks such as AWS Strands Agents, LangGraph, or similar LLM integration and fine-tuning (Claude … equivalent) Strong prompt engineering skills, including chain-of-thought reasoning RAG & Knowledge Systems Implementation of Retrieval-Augmented Generation (RAG) pipelines Experience with vector databases such as CockroachDB, Pinecone, or similar Embedding model optimisation and semantic search Context window management and chunking strategies MCP & Tool Integration Model Context Protocol ...

Engineer Required Technical Skills AWS & Generative AI: - AWS Bedrock experience (model selection, deployment, prompt engineering) - Agentic workflow experience ideally based on AWS AgentCore - Multi-agent orchestration frameworks (AWS Strands Agents, LangGraph, or similar) - Large Language Model (LLM) integration and fine-tuning - Experience with Claude, GPT-4, or similar … foundation models - Prompt engineering and chain-of-thought reasoning RAG & Knowledge Systems: - Retrieval-Augmented Generation (RAG) pipeline implementation - Vector database experience (CockroachDB, Pinecone, or similar) - Embedding model selection and optimisation - Semantic search and similarity matching - Context window management and chunking strategies MCP & Tool Integration: - Model Context Protocol ...

Engineer Required Technical Skills AWS & Generative AI:- AWS Bedrock experience (model selection, deployment, prompt engineering)- Agentic workflow experience ideally based on AWS AgentCore- Multi-agent orchestration frameworks (AWS Strands Agents, LangGraph, or similar)- Large Language Model (LLM) integration and fine-tuning- Experience with Claude, GPT-4, or similar … foundation models- Prompt engineering and chain-of-thought reasoning RAG & Knowledge Systems:- Retrieval-Augmented Generation (RAG) pipeline implementation- Vector database experience (CockroachDB, Pinecone, or similar)- Embedding model selection and optimisation- Semantic search and similarity matching- Context window management and chunking strategies MCP & Tool Integration:- Model Context Protocol ...

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 ...

Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure … OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including process ...

Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure … OpenAI, and open-source alternatives (Llama, Mistral). Experience with prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation) architectures, vector databases (Pinecone, ChromaDB, FAISS), embeddings, and building AI-powered automation solutions that leverage natural language understanding. Appian BPA Platform - Strong experience with Appian low-code platform including process ...

model registry, CI/CD for ML, feature stores, monitoring for drift, and retraining policies. Build reusable AI platform capabilities (e.g., orchestration, RAG services, prompt safety, connectors) that support multiple domains such as: Recruitment & Admissions: enquiry triage, lead scoring, document extraction, and decision support. Student Records & Registry: data quality … standards (e.g., WCAG), information security policies, and emerging AI regulations. Define and enforce guardrails for data and GenAI use: data access controls, PII handling, prompt/data leakage prevention, and content moderation. Drive adoption and change Partner with Deans, Registry, Admissions, Student Services, IT, Legal and other stakeholders ...

feedback, and creatively leveraging the capabilities provided by the internal GenAI Platform Team. You will own the entire lifecycle of an AI agent, from prompt design to production deployment and monitoring. This is a hybrid role, typically working 1 day per week at our Citigen office in London. Here … autonomous AI agents and workflows using the standardised frameworks (e.g., LangGraph, custom SDKs) provided by the central GenAI Platform Team. Master the art of Prompt Engineering to define clear, deterministic, and self-correcting agent behaviour, optimising its reasoning, planning, and task execution for specific product use cases. Develop ...

Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation … including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities ...

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 ...

generative models In-depth experience in finetuning and customizing pretrained AI models with good understanding of various patterns and practices in AI data engineering and large data processing. Handson in Prompt Engineering Azure Open AI Form Recognizer Cognitive Search Vector Databases. Develop and deliver upskilling sessions ...

regulated environments. Strong problem-solving and technical storytelling abilities. Commitment to ethical AI deployment. Key Skills Advanced Python and backend languages. Expertise in prompt engineering, fine-tuning, RAG, and agentic design. Familiarity with AI tools (GitHub Copilot, ChatGPT, SonarQube, LangChain, etc.). Understanding of observability, security, and compliance ...

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 … governance and quality controls Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, Data Version Control) Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures It Would Be Great If You Also Had Experience In Some Of These, But If Not Well Help ...

intelligent tagging and metadata enrichment frameworks to categorize and organize legal and market data, improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines. Build LLM apps using LangGraph/LangChain: tools/function calling, structured outputs … JSON Schema), agents, and multi-step reasoning. Implement ASR/TTS and multimodal where relevant (e.g., Whisper). Choose customization paths pragmatically: prompt engineering, system prompts, tools, adapters/LoRA, and selective fine-tuning only when needed. Fine-tune and optimise ML models and LLMs to enhance performance ...

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. ...

Artificial Intelligence and Machine Learning, and apply it to the problem of Enterprise Vibe Coding; Make use of techniques such as In-Context Learning (Prompt Engineering & Retrieval Augmented Generation) and Tool Calling to guide Agents to perform as intended; Work in an "eval-driven development" methodology, applying evaluation … forward ideas into practice in a large-scale project. Qualifications/What You Need To Succeed Ph.D. or MSc degree in Computer Science, Electrical Engineering, Artificial Intelligence, Machine Learning, or related technical fields is highly valued. 7+ years of work experience in Machine Learning and AI Engineering roles ...

deployment of on-premises, hybrid, and cloud-native AI solutions. GenAI Implementation: Hands-on deployment of Azure OpenAI, Vector Databases, and RAG patterns. Data Engineering: Oversee large-scale data processing using Python and PySpark to support AI model fine-tuning. Leadership: Manage technical delivery teams and deliver upskilling sessions … customer. Stakeholder Management: Gain consensus on complex technical roadmaps with diverse client groups. Technical Skills & Experience Core AI: Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold ...

deployment of on-premises, hybrid, and cloud-native AI solutions. GenAI Implementation: Hands-on deployment of Azure OpenAI, Vector Databases, and RAG patterns. Data Engineering: Oversee large-scale data processing using Python and PySpark to support AI model fine-tuning. Leadership: Manage technical delivery teams and deliver upskilling sessions … customer. Stakeholder Management: Gain consensus on complex technical roadmaps with diverse client groups. Technical Skills & Experience Core AI: Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold ...

Designing and maintaining audio data pipelines for collection, preprocessing, augmentation, and evaluation Experimenting with multimodal models that combine speech, text, and contextual signals Exploring prompt engineering, RAG, and memory architectures for voice-driven AI systems Collaborating with engineers to deploy models into low-latency, production environments Developing internal ...

tune Large Language Models (LLMs) and other generative architectures. Optimise pre-trained models (OpenAI, Anthropic, or open-source LLMs) for business use cases using prompt engineering and reinforcement learning. Experiment with model configurations to balance performance, cost, and scalability. Build robust data pipelines for continuous model improvement ...

experimentation and prototyping of advanced ML/AI techniques · Provide technical direction, mentoring, and hands-on guidance to the data science team. · Work with engineering, product, and business stakeholders to align ML strategy with business goals. · Architect and productionise end-to-end ML pipelines on Azure, while ensuring scalability … years in a technical lead role. · Deep experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with ...

workflows. You will work closely with engineers, traders, and senior stakeholders to translate real business problems into scalable AI systems.This is a hands-on engineering role, with a strong focus on production deployment, cloud infrastructure, and real-world model usage rather than pure research. Role Responsibilities Design, build … deploy AI and LLM-based solutions into production environments Work with large language models, prompt engineering, orchestration, and evaluation Integrate AI solutions into existing trading, analytics, and operational platforms Build scalable pipelines and services across multi-cloud environments (AWS, GCP, Azure) Collaborate closely with engineering, data ...

tune Large Language Models (LLMs) and other generative architectures. Optimise pre-trained models (OpenAI, Anthropic, or open-source LLMs) for business use cases using prompt engineering and reinforcement learning. Experiment with model configurations to balance performance, cost, and scalability. Build robust data pipelines for continuous model improvement ...

workshops with technical and business stakeholders Represent the organisation's technical capabilities in high-stakes client meetings Build trust and long-term relationships with engineering teams and decision-makers Solution Development & Architecture Build and iterate working AI prototypes quickly Architect scalable, maintainable systems from prototype to production Make sophisticated … 8+ years delivering complex, enterprise-grade software Proven AI/ML expertise with production deployment experience Advanced knowledge of transformer architectures, foundation models, and prompt engineering Senior stakeholder engagement experience and ability to lead high-level AI strategy ...

Developer - AI/LLM - sought by trading company based in London - Contract (Remote option available for outstanding candidates) What We're Looking For Backend Engineering Expertise 8+ years of software engineering experience with strong Java backend skills. Proven track record in modernising production systems and designing APIs/… Code, GitHub Copilot) and Model Context Protocol (MCP). Experience integrating AI into CI/CD pipelines and building AI-powered automation. Knowledge of prompt engineering, model selection, and LLM capabilities. Proven AI Impact Demonstrated success in using AI to improve productivity and code quality. Experience with ...