101 to 125 of 928 LLM Jobs in the UK

proficiency in Python 3+ years of experience with any of the following fundamental AI technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems, etc Familiarity with cloud services and MLOps tooling to deploy and scale data and ML workloads cost-effectively Familiarity with data warehouses (Redshift, BigQuery, Snowflake, etc) and More ❯

a measurable impact. What you'll be doing: Collaborating with business teams to uncover and define AI/automation opportunities. Engineering and optimising prompts to ensure consistent, high-quality LLM outputs. Building and deploying AI-powered workflows that connect LLMs with business applications, APIs, and automation tools. Implementing RAG (Retrieval-Augmented Generation) pipelines to integrate enterprise data. Rapidly prototyping and More ❯

/React Native + Python/Django is our stack, but we’re happy for you to learn). Hands-on experience or strong interest in agentic AI systems, LLM-powered automation, or intelligent workflow tools. Have worked with large enterprise IT departments as a vendor of Enterprise SaaS products Demonstrated ability to pick up new technologies quickly and deliver More ❯

We are looking for: Experience supporting pre-sales activities in a consultancy or product-led environment Strong understanding of AI/ML techniques, such as reinforcement learning, planning algorithms, LLM-based agents, and simulation environments Proven experience in designing and developing agentic systems for production environments, including autonomous agents, multi-agent coordination, and decision- making frameworks Detailed knowledge of the More ❯

We are looking for: Experience supporting pre-sales activities in a consultancy or product-led environment Strong understanding of AI/ML techniques, such as reinforcement learning, planning algorithms, LLM-based agents, and simulation environments Proven experience in designing and developing agentic systems for production environments, including autonomous agents, multi-agent coordination, and decision- making frameworks Detailed knowledge of the More ❯

debate, align to unified decisions. Own operability: set up and maintain CI/CD, monitoring/alerting, performance & error budgets, and safe rollback paths. Build and integrate AI features (LLM/agent workflows, RAG/vector DB integration, eval hooks, cost/safety guardrails). Essential Requirements 3-6+ years building production backends/services , with shipped work and More ❯

debate, align to unified decisions. Own operability: set up and maintain CI/CD, monitoring/alerting, performance & error budgets, and safe rollback paths. Build and integrate AI features (LLM/agent workflows, RAG/vector DB integration, eval hooks, cost/safety guardrails). Essential Requirements 3-6+ years building production backends/services , with shipped work and More ❯

growing FinTech in London who are building the next generation of AI based financial products. We are looking for Senior Software Engineers who have commercial experience with GenerativeAI and LLM integrations. You will be building Gen AI frontend agents and working with hybrid codebases with hosted prompts. This is a full stack opportunity working in their Gen AI team, working More ❯

growing FinTech in London who are building the next generation of AI based financial products. We are looking for Senior Software Engineers who have commercial experience with GenerativeAI and LLM integrations. You will be building Gen AI frontend agents and working with hybrid codebases with hosted prompts. This is a full stack opportunity working in their Gen AI team, working More ❯

Strong problem-solving skills; capable of delivering scalable, maintainable software. Effective communicator and team player. Knowledge of monitoring/alerting best practices for GenAI pipelines (e.g., Langsmith, Langfuse) and LLM-as-a-judge. Cloud experience (AWS, GCP) and familiarity with DevOps practices (CI/CD, Docker, Kubernetes, IaC). Experience with event-driven architecture and streaming (Kafka a strong plus More ❯

Strong problem-solving skills; capable of delivering scalable, maintainable software. Effective communicator and team player. Knowledge of monitoring/alerting best practices for GenAI pipelines (e.g., Langsmith, Langfuse) and LLM-as-a-judge. Cloud experience (AWS, GCP) and familiarity with DevOps practices (CI/CD, Docker, Kubernetes, IaC). Experience with event-driven architecture and streaming (Kafka a strong plus More ❯

production-ready solutions. Ideal Candidate Hands-on experience with AI/ML tools (e.g. NLP, predictive modelling, process automation). Familiarity with cloud platforms (AWS, Azure, or GCP). LLM experience Strong problem-solving and collaboration skills. Ability to communicate technical concepts clearly to non-technical audiences. Passionate about applying AI responsibly and effectively in business contexts. Benefits Hybrid working More ❯

production-ready solutions. Ideal Candidate Hands-on experience with AI/ML tools (e.g. NLP, predictive modelling, process automation). Familiarity with cloud platforms (AWS, Azure, or GCP). LLM experience Strong problem-solving and collaboration skills. Ability to communicate technical concepts clearly to non-technical audiences. Passionate about applying AI responsibly and effectively in business contexts. Benefits Hybrid working More ❯

production-ready solutions. Ideal Candidate Hands-on experience with AI/ML tools (e.g. NLP, predictive modelling, process automation). Familiarity with cloud platforms (AWS, Azure, or GCP). LLM experience Strong problem-solving and collaboration skills. Ability to communicate technical concepts clearly to non-technical audiences. Passionate about applying AI responsibly and effectively in business contexts. Benefits Hybrid working More ❯

but operating as a tech lead in a flat structure. What they’re after: 5+ years’ experience building enterprise-grade software (Python, microservices, distributed systems) Proven track record deploying LLM-based applications Clear evidence of Software skills (CI/CD etc.) Ability to lead small teams, own solutions end-to-end, and mentor engineers Strong communicator with experience working in More ❯

but operating as a tech lead in a flat structure. What they’re after: 5+ years’ experience building enterprise-grade software (Python, microservices, distributed systems) Proven track record deploying LLM-based applications Clear evidence of Software skills (CI/CD etc.) Ability to lead small teams, own solutions end-to-end, and mentor engineers Strong communicator with experience working in More ❯

division headed up by well-regarded CDO who comes from a ‘hands on’ Data Science background. The Data Unit is filled with experienced Data Scientists, Analyst, Machine Learning Engineers, LLM specialists, and Data Engineers. Given the quality of the team involved, instant exposure to more technical projects and colleagues, and the excellent working environment that this company provides, I would More ❯

Key Responsibilities Design and deliver AI & data strategies across portfolio companies and internal teams Lead technical diligence on AI-readiness and opportunities during deal evaluation Build and deploy reusable LLM/AI/ML systems (agents, copilots, etc.) to unlock value Define governance frameworks across risk, explainability, audit, and compliance Own internal AI transformation—deploying tools, platforms, and training programmes More ❯

Key Responsibilities Design and deliver AI & data strategies across portfolio companies and internal teams Lead technical diligence on AI-readiness and opportunities during deal evaluation Build and deploy reusable LLM/AI/ML systems (agents, copilots, etc.) to unlock value Define governance frameworks across risk, explainability, audit, and compliance Own internal AI transformation—deploying tools, platforms, and training programmes More ❯

Knowledge of financial data and systems (Bloomberg, SimCorp Dimension) preferred. Understanding of investment management workflows (portfolio management, risk, compliance, performance reporting). Experience with GitHub and AI tools (OpenAI, LLM APIs, agentic workflows). Qualifications: Bachelor’s degree in Computer Science, Quantitative Finance, Data Engineering/Analytics/Science, or related field. 2+ years of experience in data engineering, BI More ❯

Knowledge of financial data and systems (Bloomberg, SimCorp Dimension) preferred. Understanding of investment management workflows (portfolio management, risk, compliance, performance reporting). Experience with GitHub and AI tools (OpenAI, LLM APIs, agentic workflows). Qualifications: Bachelor’s degree in Computer Science, Quantitative Finance, Data Engineering/Analytics/Science, or related field. 2+ years of experience in data engineering, BI More ❯

ways of working across mixed client-consultancy teams. 💡 About You Proven experience as a Product Manager in AI, data, or enterprise technology environments. Hands-on exposure to AI MVPs, LLM applications, or applied ML use cases (e.g. RAG, copilots, generative search). Strong technical grounding in vector search, embeddings, APIs, data pipelines, and prompt design. Skilled in navigating complex enterprise More ❯

technical expertise with strategic client engagement. As a Solutions AI Architect, you will: Lead the design and delivery of AI and cloud-native architectures, including Generative AI, NLP, and LLM solutions. Act as a trusted advisor to senior stakeholders, guiding AI roadmaps and strategy. Translate complex business needs into scalable AI-driven solutions across public cloud, edge, and hybrid environments. More ❯

e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI based projects. Ability to scope and structure solutions around ambiguous business problems, turning them into tractable pipelines Confident in managing small technical teams, reviewing work, and setting standards More ❯

and supporting delivery on key technical initiatives. Establish engineering best practices across performance, reliability, and security. Oversee the design and implementation of AI-driven systems — including multi-agent orchestration, LLM integration, and data pipelines (LangChain, LangSmith, vector databases). Drive continuous improvement in CI/CD, cloud infrastructure, and deployment processes (Docker, Kubernetes, AWS). Mentor engineers, recruit top talent More ❯