1,351 to 1,375 of 2,918 LLM Jobs in England

production-quality tooling that accelerates offensive security workflows, integrated directly into the watchTowr Platform and our autonomous pipelines Design, experiment with, and iterate on LLM-powered systems, agents, and automations for vulnerability discovery, exploit reproduction, and analysis Develop and refine the orchestration layers that turn AI capability into reliable, repeatable ...

meeting you booked from a cold call. AI‐automated outbound. You built automated outbound workflows with AI tools (Clay, Apollo, n8n, or LLM prompts). Show us: a workflow you built, the tools behind it, and what it produced. Pipeline generation. You generated B2B/enterprise pipeline. Show us: your ...

trust-based relationships at the senior level. Growth Ownership: Drive a 20% YoY growth target by identifying commercial opportunities in Paid Media, Social Organic, LLM, and Influencer strategy. Matrix Orchestration: Lead the "Trio" (Account, Program, Strategy), serving as the final decision-maker to ensure delivery matches client expectations. Strategic Sparring ...

supply, demand, and market conditions Predictive demand and routing models that forecast driver availability and optimise job allocation before a customer even books LLM-powered tooling across our internal and customer-facing products, from intelligent quoting to driver workflow automation A two-sided marketplace where drivers can buy and sell ...

etc.) and with security review processes (SOC 2, ISO 27001, HIPAA, FedRAMP). Experience running on or supporting Bedrock/Vertex/multi-cloud LLM deployments. Experience with regulated customers (financial services, healthcare, public sector) and delivering alongside SI/GSI partners. A track record of public technical communication: YouTube ...

through to deployment of standalone, customer‐facing products. The ideal candidate is equal parts researcher, engineer, and product builder. You bring authoritative depth in LLM customisation and alignment, a sharp instinct for performance and quality, and the ability to ship end‐to‐end AI‐powered products that meet Apple … Apple. In this role, you will own the end‐to‐end lifecycle of an internal generative AI system at global scale - from pre‐training LLM strategies and reinforcement learning from human feedback (RLHF) through fine‐tuning, alignment, evaluation, and production deployment. You will architect and deliver standalone AI‐powered products ...

your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into … reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction ...

Core platform - the services and infrastructure that let us deploy to a multitude of public cloud providers and that powers many ML and LLM powered features. We give every other engineering team a reliable base to build on, and we own the software delivery lifecycle end to end: the tooling … exciting opportunity to grow professionally while contributing to a mission-driven organization. Responsibilities What you’ll own Reliability of platform(includes ML and LLM workloads) - model serving and inference infrastructure (GPU-backed endpoints, autoscaling, latency and cost tradeoffs), with SLOs, on-call, and incident response that cover models, not just ...

operationalize Comply's semantic layer — turning the ontological models defined by our ontologist and architects into working knowledge graphs, vector search infrastructure, and LLM-powered pipelines. This is a hands-on engineering role at the intersection of knowledge representation, AI infrastructure, and data platform engineering. You will own the delivery … financial and regulatory data invector spaceBuild and operate vector database infrastructure for semantic search and similarity retrievalImplement RAG (Retrieval-Augmented Generation) architectures that ground LLM outputs in Comply'sproprietary dataEvaluate and integrate LLM tooling and frameworks appropriate to Comply's use casesData Pipeline & Platform EngineeringBuild reliable, observable data pipelines that ...

that can operate within the company's wider technology ecosystem. You will be involved in: Designing and developing AI agents and agentic workflows Building LLM-powered applications and automation Integrating AI with existing CRM, PMS, databases, APIs and internal systems Developing AI solutions that can reason, retrieve information, make decisions … looking for someone who has genuine commercial experience building AI solutions, rather than someone who has simply experimented with ChatGPT or integrated an LLM API. You may have a background as an AI Engineer, Generative AI Engineer, Machine Learning Engineer, Software Engineer or AI Solutions Engineer, but you will have ...

Job Introduction Handelsbanken is a relationship bank built on trust, long-term thinking and local decision-making. We provide bespoke banking and wealth management services to personal and corporate customers. Our decentralised model means decisions ...

CAPGEMINI INVENT At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive ...

driving further adoption of cloud first technologies; we are Azure based, with PostgreSQL and MongoDB as our primary data stores and a multi-provider LLM stack (OpenAI, Google Gemini and Anthropic). We want you to dive in, get your hands dirty, and figure things out, but also … setting objectives and assisting with tailored development plans Our engineering environment includes technologies such as Python (FastAPI), LangChain/LangGraph for multi-agent LLM orchestration, React/TypeScript, PostgreSQL, MongoDB, Redis, Azure (App Service, Container Registry, Blob Storage), Docker, GitHub Actions, and modern CI/CD pipelines. About ...

language and technology and who are keen to use their technical abilities to develop automated, scalable solutions to challenges in the Large Language Model (LLM) space. Applying a combination of expertise in LLMs, coding, and natural language, they will overcome complex problems in model evaluation, automation, and context engineering … should also have exceptional writing and communication skills with the ability to interface between both technical and non-technical teams. Key job responsibilities- Develop LLM-as-a-judge systems to support Human-in-the-loop evaluations- Automate operations and perform data analysis using scripting languages (e.g. Python)- Author, optimize ...

workbenches Tech stack: Java, Python, AngularJS, Angular AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference. Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models Collaborate with research teams on innovative machine learning ...

self‐service AI tools. Contributing to documentation supporting responsible AI and governance practices. About you Proven experience building and deploying production‐grade AI and LLM‐powered applications, ideally using Python. Hands‐on experience with leading LLM platforms such as AWS Bedrock, OpenAI, Anthropic, or similar technologies. Strong understanding of retrieval ...

multi-step AI agents that reason over unstructured data, assess risk, and drive real business outcomes. We're using frameworks like LangChain to orchestrate LLM-driven services that sit at the heart of how the business operates. The problems are genuinely hard: ambiguous inputs, high-stakes decisions, and the kind … maintain business-critical AI agent services. Build tailored agent workflows and services from business requirements, using LangChain and related frameworks with reliable patterns for LLM-driven decision-making in production. Integrate tests and validation to improve AI agents through evals and monitoring. Work with software engineers and architects to lead ...

depth across the modern AI engineering stack is essential, not just RAG in isolation: Semantic search, vector/embedding infrastructure, and retrieval architecture design LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) LLM evaluation, guardrails, and red-teaming tooling (hallucination detection, safety/bias ...

drive experimentation, modeling, and evaluation, partnering closely with engineers to translate validated approaches into scalable, customer-facing solutions. Key Responsibilities: Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies, patent search). Define agentic workflows and reasoning strategies for multi-step IP tasks. Develop retrieval strategies … needs. Requirements: Degree in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.). Strong experience in machine learning, NLP, and LLM-based modeling. Strong experience designing and running experiments, including model evaluation and iteration. Strong coding skills in Python. Experience with generative AI techniques (e.g., prompt ...

Amazon Web Services, Business Development, CI/CD, CloudFormation, DAMA, Data Architecture, Decision Intelligence, DevOps, Generative AI, Google Cloud Platform, Hybrid Cloud, Large Language Model Applications, Machine Learning, Microsoft Azure, TOGAF, Terraform, Thought Leadership, Transformation RoadmapsData & AI Strategy Consultant/Architect – AI Transformation (GenAI & Agentic AI)Are you ready … adoption of GenAI, copilots, and agentic AIArchitect intelligent cloud and hybrid ecosystems, supporting the modernisation of legacy data environmentsDesign and implement agentic AI workflows, LLM-based applications, and decision intelligence platformsDrive automation through DevOps practices, CI/CD pipelines, and Infrastructure-as-Code (Terraform, CloudFormation)Develop enterprise data ...

production, including state management, task execution, model routing, retries and observability. Support AI Infrastructure: Work closely with our AI engineers supporting production NLP, LLM and quantitative model workloads, including our in-house GPU infrastructure. Automate Infrastructure: Build and manage Infrastructure-as-Code using Pulumi and automate deployments through GitHub Actions. … Proactive, resourceful and comfortable taking ownership in a fast-moving engineering environment. Bonus : with Apache Airflow, real-time data platforms, AI/ML infrastructure, LLM agents, GPU infrastructure or financial-market systems. Why Permutable Real Ownership: Take significant ownership of our production architecture and infrastructure. Build the Next Generation: Help ...

solutions that power AI-driven case management capabilities. Build, implement and optimise data pipelines that connect enterprise applications and systems with AI and large language model platforms. Create, refine and optimise prompts and AI workflows to improve the quality, accuracy and relevance of AI-generated outputs. Support and drive … work independently, take ownership of technical initiatives and provide leadership within a multidisciplinary team. Additional Skills & Qualifications experience with Gemini or other large language model platforms. experience working with Google Cloud Platform (GCP). Hands-on experience in agentic AI development and orchestrating agent-based workflows. Knowledge of AI-assisted ...

vendor availability. Event-driven consistency. Services coordinating over Pub/Sub — sagas across offer → contract → tenancy → payment with no distributed transaction to lean on. LLM tool calling, deterministic API calls, and other intra‐and inter‐service communications all running across the same coordination system. AI harnesses in production. Deploying agentic … into real-world operational settings — acting on real money, tenancies and legal exposure, with the guardrails, observability and correctness that demands. Non-deterministic LLM working within compliant, secure deterministic software. Our stack We build on NestJS + TypeScript on GCP/GKE , with MongoDB , Redis and GCP Pub/ ...

Kubernetes/EKS, ECS, Docker, RDS/PostgreSQL and S3. Productionise AI Workloads: Work closely with our AI engineers to deploy and operate NLP, LLM and quantitative‐model workloads, including workloads using our in‐house GPU infrastructure. Own Software Through to Production: Take responsibility for testing, deployment, performance, monitoring … comfortable taking responsibility in a small, fast‐moving engineering team. Experience with Apache Airflow, Kubernetes, real‐time data platforms, AI/ML infrastructure, LLM agents, GPU infrastructure or financial‐market systems would be useful, but is not essential. Why Permutable? Real Ownership: Take responsibility for important production systems and influence ...

leveraging frameworks such as Next.js or Vite. GenAI Frameworks: Familiarity with tools like LangChain, LangGraph, CrewAI, or Vercel AI (in Python or JavaScript). LLM experience: Practical experience with Large Language Models (LLMs) such as OpenAI, Anthropic, Mistral, or Llama, and tools like Ollama. Cloud Platforms: Proficiency … Orchestration: Hands-on experience with Docker, Kubernetes, and Docker Compose. Infrastructure as Code (IaC): Exposure to tools like Terraform. Monitoring Tools: Familiarity with LLM monitoring tools like Langsmith, Langfuse, or similar. CI/CD: Experience with continuous integration and deployment tools such as GitLab, GitHub, or Jenkins. Database Management Vector ...