1 to 25 of 43 Permanent Prompt Engineering Jobs in Central London

Job Title: Prompt Engineer/AI Engineer Location: London About GIMO: Global Interactive Marketing Online (GIMO) Global Interactive Marketing Online (GIMO) is a London-based leading independent marketing agency and software developer within the iGaming industry. GIMO works in close partnership with leading global gaming brands such as NetBet, 777, and betFIRST. About Netbet Brand: Since 2006, NetBet has … line with the rules and regulations of each jurisdiction and that players receive the best possible service. Role Overview: We are seeking an innovative and detail-oriented mid-level Prompt Engineer & AI Engineer to enhance our AI-driven applications. This role is crucial for designing, testing, and refining the prompts that power our large language models (LLMs) and for … Design, build, test, and refine high-quality prompts to steer LLMs toward desired outputs and behaviors for key business applications. Conduct thorough analysis of model responses and perform iterative prompt engineering to improve accuracy, tone, and overall performance. Develop, test, and maintain Python scripts and applications, particularly within collaborative platforms like Replit, to support AI systems and streamline More ❯

that automate processes, improve speed, and enhance decision-making. Role Responsibilities As a Senior AI Applied Engineer, you will: Build & Deploy AI-Driven Software Solutions You'll blend software engineering and AI expertise to develop scalable, production-grade systems leveraging generative AI and agentic automation. Own Project-Based Work Across Diverse Domains You'll tackle varied engagements, ranging in … teams, translating client needs into technical solutions, requiring strong communication and stakeholder-facing capabilities. Leverage Generative AI Expertise Utilise your hands-on experience with generative AI tools or workflows, prompt engineering, LLM integration, or similar, but the emphasis is on engineering implementation and delivery. Who We're Looking For Essential Qualifications & Experience Strong software engineering background … with deep experience deploying scalable systems At least some commercial experience using Generative AI exposure (e.g., LLMs, agentic interfaces, prompt engineering) but primarily strong engineering fluency Comfortable with project-based, delivery-focused work, even if no prior consultancy experience Confident in client-facing situations and able to collaborate effectively with non-technical stakeholders Reliable, consistent work history More ❯

Thought Leadership: Produce thought leadership content, refine go-to-market propositions, and maintain strong knowledge of the competitive landscape. Collaboration: Work closely with cross-functional teams—including data science, engineering, and business stakeholders—to identify opportunities and design robust AI solutions. Foster cross-functional collaboration between various stakeholders like business, data science, and engineering. Innovation: Contribute to overall account … and cost optimizations. Your Profile: Essential skills/experience/knowledge: Experience in architecting and solutioning in Gen AI, Agentic AI, classic ML, and automation space. Good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA … LangGraph). Strong working knowledge and practical deployment experience on at least one major cloud platform (AWS, Azure, GCP), including their AI/ML services. Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow More ❯

of reasoning planning and autonomous decision-making Integrate thirdparty libraries and tools such as Hugging Face Transformers Crew AI and Microsoft Agent Framework Ensure best practices in model governance prompt engineering and responsible AI Proven experience on advanced agentic AI implementation using MCP Servers and using A2A Framework Mentor junior engineers and contribute to the AI strategy and … similar platforms Proficiency in Python and familiarity with AI frameworks like LangChain LangGraph Semantic Kernel Autogen and Crew AI Experience with Hugging Face models and deployment pipelines Knowledge of prompt engineering vector databases and retrieval augmented generation RAG Excellent problem solving communication and collaboration skills Preferred Qualifications Certifications in Azure AI or Microsoft AI Engineer Associate Experience with More ❯

Develop scalable backend systems to support autonomous decision-making and communication between agents. Monitor, evaluate, and continuously improve agentic performance and reliability. Skills & Experience Essential: 3+ years in software engineering, AI engineering, or machine learning roles. Strong programming skills (Python preferred). Experience with LLM integration (e.g., OpenAI, Anthropic, Hugging Face). Understanding of agentic frameworks, prompt engineering, and orchestration tools. Familiarity with APIs, databases, and cloud infrastructure (AWS, Azure, or GCP). Desirable: Experience in small, agile teams or start-up/SME environments. Knowledge of vector databases, RAG systems, or AI orchestration platforms. Interest in autonomous systems, cognitive architectures, or workflow automation. More ❯

Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: Chatbots Document Q&A systems Report generators Code assistants Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java … experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. … MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. Nice-to-Have Skills Description: n/a Languages: English: C1 Advanced More ❯

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, Retail, Services & Medias, Public Services & Government. With a team of … Required Technical Skills Machine Learning , 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 development tools (e.g., GitHub Copilot … Tabnine). Familiarity with data platforms like Dataiku, Databricks. Strong software engineering fundamentals (Python preferred; others welcome). Key Skills & Experience Ideally 5+ years of professional experience, including 3+ years in AI and data science with evidence of practical, real-world contributions. Master's degree (or higher) in Computer Science, Data Science, Engineering, or a related discipline with More ❯

AI Engineer - Elite Sports Tech - London AI Engineer needed to join a highly skilled Engineering & AI team in a rapidly growing sports tech company. Role and Responsibilities: Design, build, and deploy Large Language Model (LLM)-driven applications into production Develop retrieval-augmented generation (RAG) systems for real-time insights from performance and wearable data Optimise and fine-tune LLMs … and scalable backend components in Python Collaborate cross-functionally with engineers, data scientists, designers, and product managers to ship AI-first features Requirements: 2+ years of hands-on AI Engineering experience, with strong software engineering fundamentals Proven experience working with LLMs in production (fine-tuning, prompt engineering, or API integrations) Proficiency in Python Experience designing and More ❯

Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy and relevance. Integrate AI models with enterprise systems, APIs, and data stores using Python, Java … experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools and practices (e.g. … MLflow, Kubeflow, Vertex AI, Azure ML). Strong understanding of data engineering, data pipelines, and ETL workflows. Excellent problem-solving, communication, and stakeholder engagement skills. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field. Luxoft is committed to fostering a diverse and inclusive workplace. We show fairness to all throughout our More ❯

HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered on digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media … wider enterprise architecture. Technical Skillset Requirements Core AI & Frameworks: Agentic Frameworks: Expert-level knowledge of agentic frameworks such as LangChain, LangGraph, Google Agent Development Kit (ADK) LLM Expertise: Advanced Prompt Engineering and hands-on experience with model fine-tuning techniques including PEFT and QLoRA. Proven experience with models like Gemini, and Llama 3. RAG & Vector Databases: Deep expertise … in RAG architecture and evaluation metrics. Proven experience with Vector Databases such as Milvus, Pinecone, or Chroma. Software & Cloud Engineering: Programming & APIs: Expert-level Python and demonstrable experience building production services with FastAPI. Cloud Platform: Mastery of GCP, particularly Vertex AI, Google Kubernetes Engine (GKE), and Cloud Functions. Databases: Strong command of relational databases like PostgreSQL and familiarity with More ❯

for a leading research platform. This is a hands-on role focused on production-grade LLM applications, AI-enabled workflows, and augmented intelligence solutions. You will collaborate closely with engineering, research, analytics, and product teams to drive innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval: Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG … NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization; ensure scalable, reliable, and business-aligned AI solutions. - Platform & Operations (MLOps): Deploy and operate services on Azure; implement CI/CD and … Infrastructure as Code; add monitoring, logging, and observability; ensure reliability, fault tolerance, and performance optimization. - Governance & Security: Enforce data privacy, ethical AI practices, and access controls; mitigate risks like prompt injection; establish model versioning, bias mitigation, and reproducibility best practices. - Software Engineering & Collaboration: Write clean, maintainable code; contribute to architecture, POCs, and production services; mentor junior engineers; stay More ❯

Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL). - Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions. - Design and conduct hypothesis testing (A/B and multivariate testing) and apply causal inference methodologies. - Perform exploratory data analysis, feature engineering … detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation engines). - Partner with engineering teams to ensure robust deployment and adherence to MLOps principles. - Shape and consult on broader data strategy and infrastructure. - Mentor and coach junior team members while staying ahead of … machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering, embeddings, vector search, etc. - Skilled in managing complex codebases (Git) and working with cloud platforms (GCP, AWS). - Excellent analytical, communication, and organisational skills. Desirable - MS/ More ❯

experience with LangGraph (bonus: contributions to the open-source project) Strong background in Python, LangChain, OpenAI APIs, and LLM architectures Familiarity with vector databases, retrieval-augmented generation (RAG), and prompt engineering Understanding of software design principles, version control (Git), and CI/CD practices Creative problem-solver with a bias toward action and experimentation Nice to Have Experience … deploying AI agents at scale Knowledge of cloud platforms (AWS, GCP, Azure) Background in data engineering, NLP, or ML Ops Why Join Us Work on cutting-edge AI projects with real-world impact Collaborate with a world-class engineering team Flexible remote environment with strong growth potential Competitive salary, equity options, and great benefits If you are interested More ❯

stack development and AI system design to complex enterprise environments. This role demands hands-on experience in building and deploying AI/ML solutions, a strong grasp of software engineering principles, and proficiency with cloud platforms. You will play a key role in developing scalable, intelligent systems that drive innovation and deliver measurable business value. Your Responsibilities: Full Stack … with AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). Experience with state-of-the-art LLMs (e.g., GPT series, Llama series, Mistral, Claude), including prompt engineering, fine-tuning, and evaluation. Hands-on experience with core GenAI frameworks (e.g., LangChain, LlamaIndex) and Agentic AI frameworks (e.g., AutoGen, CrewAI, LangGraph). Proficiency in MLOps/… MLflow, Kubeflow, Docker, Kubernetes). Strong working knowledge and practical deployment experience on major cloud platforms (AWS, Azure, GCP), including their AI/ML services. Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Experience in designing and implementing enterprise-grade AI solutions, including RAG-based solutions with LLMs and vector databases (e.g. More ❯

Scikit-learn, and Hugging Face 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 modelling, interface design, expression rules, integration objects, and data modelling. Skilled in building end-to … scraping, and legacy system integration. Ability to assess when RPA vs. API integration vs. AI solutions are most appropriate, and experience building hybrid automation solutions combining multiple technologies. Data Engineering & Pipeline Development - Strong skills in building data pipelines for AI/automation solutions including data extraction, transformation, and loading (ETL). Experience with SQL databases (SQL Server), data validation More ❯

across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring model performance in production Automation Architecture Deep knowledge of automation tools including GitHub Actions, Terraform, and … with business process automation (RPA) tools like Appian Workflow orchestration experience (Airflow, Prefect) Ability to build custom automation frameworks using Python or similar languages Full-Stack Development Solid software engineering background with proficiency in Python, JavaScript/TypeScript, Java, or Go Experience with modern frameworks (React, Node.js, Django, FastAPI) Knowledge of microservices architecture, API design (REST, GraphQL) Experience with More ❯

to reinvent how internal business systems and data work together. As a Staff Software Engineer (AI/ML) , you’ll be the technical lead for a newly formed AI Engineering function . You’ll build and scale AI-powered backend systems that connect enterprise data platforms (CRM, analytics, and communication tools) with large language models — creating intelligent tools and … deliver high-value AI applications. Mentor engineers and shape the company’s approach to internal AI enablement. What You’ll Bring 7+ years’ experience in backend or full-stack engineering, ideally within a SaaS or data-driven business. Strong knowledge of LLMs , prompt engineering, and fine-tuning approaches. Hands-on experience with AI/ML pipelines and … Hybrid working with a central London office (bike storage and showers available) “Work from Abroad” policy (up to 5 days per year) Pension scheme Collaborative, inclusive, and forward-thinking engineering culture Strong focus on career development and ownership More ❯

services that support AI agent interaction. Implement APIs, contracts, and metadata aligned with the Model Context Protocol. Develop internal tooling that supports AI-native workflows. Establish best practices for prompt engineering, model fine-tuning, and evaluation. Stay current with developments in AI/ML and apply relevant research to product needs. Participate in design reviews, code reviews, and … incident response. Qualifications Bachelor’s degree in Computer Science, Engineering, or equivalent. Required Skills Software development experience with proven expertise in at least one programming language (Python/Java/Typescript) with experience building APIs and integrating backend systems. Solid Machine Learning fundamentals. Model Context Protocol for managing context and tool interfaces for agents. LLM integration patterns, including prompt More ❯

Responsibilities Collaborate with client teams to understand domain challenges and success metrics. Translate business requirements into scalable AI solutions using the agentic framework. Prototype and deploy LLM-based agents (prompt structures, orchestration logic, memory, retrieval pipelines). Drive the transition from proof-of-concept to production with reliability and measurable ROI. Act as a trusted technical advisor, guiding adoption … and defining success metrics. Contribute reusable components and frameworks for faster deployments. Qualifications 3+ years building production-grade AI/data solutions. Hands-on GenAI experience (LLMs, prompt engineering, RAG, vector databases, agentic frameworks like LangChain, LlamaIndex, DSPy). Strong Python proficiency with a GitHub portfolio showcasing MLE or GenAI projects. Expertise in Machine Learning Engineering (model … impact. Why Join? Shape how financial institutions adopt and scale agentic AI. Move beyond prototypes—deploy real-world GenAI systems. Work directly with founding leadership, influencing product evolution. Blend engineering excellence, product innovation, and customer impact. Interested? Apply now or reach out to Gravitas for a confidential discussion. More ❯

components into business workflows. YOUR PROFILE Hands-on software development experience. Strong backend development skills. Proven experience with containerization (ECS, Fargate, Docker, Kubernetes). Experience with LLMs, vector databases, prompt engineering, and multi - agent frameworks, and distributed training on SageMaker, SLM fine-tuning. Strong experience with AWS, including deploying and managing cloud-native applications. Excellent communication and stakeholder … unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of €22.5 More ❯

workflows, and Power Platform concepts including Power Automate, Power Apps, and Dataverse Experience tunning LLMs on Microsoft Azure ML Studio/Azure AI Foundry and applying Generative AI and prompt engineering techniques. Strong understanding of AI governance, observability, and compliance frameworks. Proven ability to deliver secure, scalable, and responsible AI solutions. Excellent communication and presentation skills. Extensive experience More ❯

Senior LLM Engineer – London | Hybrid (2 days per week on-site, Bank area) My client is a long-established consultancy that originally built its reputation in data engineering and wider data transformation, and over the past few years has grown a strong applied AI practice. They tend to work with UK organisations where data security, reliability and explainability actually … you’ll be doing: • Owning the design and build of LLM-based systems end-to-end • Fine-tuning and adapting models (LoRA, instruction tuning, PEFT etc) rather than just prompt-engineering • Building RAG workflows, embedding strategies, memory layers and domain grounding • Working out how to measure output quality, reduce hallucination risk and improve robustness • Optimising inference performance (quantisation More ❯

re partnering with a stealth-mode deep tech AI lab based in London that’s building foundation models from the ground up . This isn’t fine-tuning or prompt engineering, it’s genuine model pre-training, post-training, and large-scale systems research. The company secured substantial funding in early 2025 from top-tier institutional VCs and … Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO, or alignment optimisation). Solid software engineering fundamentals - version control, CI/CD, and production-grade model deployment. Experience working in cloud-native or high-performance compute environments (AWS, GCP, Docker, Kubernetes). A curiosity for More ❯

back to Product to shape the reporting roadmap Product Collaboration & Innovation (20%) Shape AI reporting features: Partner with Product and Data Science to spec new capabilities—structured output schemas, prompt templates, embedding-based discovery Experiment & prototype: Build proof-of-concepts for new report types using Python, pandas, OpenAI APIs, and our data pipelines QA & iteration: Test new features, validate … Great FitTechnical Foundation 5+ years in analytics roles building customer insights, product analytics, or data-driven reporting AI-native experience: Hands-on work building reports or products using LLMs—prompt engineering, structured output generation, embeddings, RAG, summarization pipelines Python proficiency: Comfortable with pandas, OpenAI library, API integrations, and data manipulation for prototyping and analysis SQL fluency: Can write More ❯

mixed ability. Bonus points for: Experience with NLP/LLMs, Computer Vision or Generative AI Formal teaching qualification or EPA assessor experience Hands-on exposure to responsible AI or prompt engineering Why join? You'll be part of a mission-driven organisation known for making cutting-edge technology understandable and exciting. Learning culture: Dedicated learning calendar and quarterly More ❯