176 to 200 of 2,311 LLM Jobs in London

Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse, together with solution management, environments and application lifecycle management. Experience building and orchestrating LLM agents, including prompt design, grounding and retrieval, structured outputs, and testing and evaluating agent behaviour where outputs are uncertain or non-deterministic. Experienced with cloud ...

Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse, together with solution management, environments and application lifecycle management. Experience building and orchestrating LLM agents, including prompt design, grounding and retrieval, structured outputs, and testing and evaluating agent behaviour where outputs are uncertain or non-deterministic. Experienced with cloud ...

Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse, together with solution management, environments and application lifecycle management. Experience building and orchestrating LLM agents, including prompt design, grounding and retrieval, structured outputs, and testing and evaluating agent behaviour where outputs are uncertain or non‐deterministic. Experienced with cloud ...

well‐structured production code. Qualifications – Nice to Have Experience with streaming or queuing systems (Kafka, Pub/Sub, SQS). Familiarity with AI/LLM systems (AOE integration), though not required across all charters. Knowledge of data engineering patterns or ETL/ELT workflows. Prior experience with API gateway architectures ...

looking for? Strong and demonstrable experience and knowledge of oC#/.NET oNon-relational databases (CosmosDB, Table Storage) Knowledge of building Generative AI/LLM powered solutions would be advantageous (OpenAI, Azure AI Foundry, AWS Bedrock, Google Vertex) Knowledge of effective use of agentic coding tools and techniques Ability ...

workflows that include SAST, DAST, policy enforcement, and performance telemetry. Improving reliability and resilience through SLOs, error budgets, and chaos engineering. Working knowledge of LLM‐based services and AI infrastructure. You don't need to be an ML engineer, but you should be comfortable deploying, securing, and operating AI Gateways ...

capabilities, including: Agentic AI platforms, AI assistants, copilots and autonomous workflows Multi-agent systems incorporating reasoning, planning, memory, orchestration and tool integration Production-grade LLM and RAG architectures Intelligent search, knowledge assistants, workflow automation and decision-support systems Enterprise LLMOps, MLOps, observability and AI governance AI security, guardrails, evaluation … years of software engineering, architecture or platform leadership 8+ years delivering AI/ML platforms into production Proven experience architecting and deploying Agentic AI, LLM and Generative AI solutions at enterprise scale Strong experience with RAG and LLM application architectures A background within banking, financial services or another highly regulated ...

scalable, secure, maintainable, and aligned with business objectives. Provide deep expertise in model development, experimentation, optimization, evaluation, and production deployment. Establish standard methodologies for LLM evaluation, model benchmarking, AI quality measurement, and performance assessment. Evaluate emerging AI technologies, foundation models, and third-party solutions to find opportunities for innovation … Learning solutions at scale. Deep expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures. Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment. Good foundation in statistics, probability, optimization, experimentation, and applied machine learning. Advanced proficiency ...

maintainable, and aligned with business objectives**.* Provide deep expertise in **model development, experimentation, optimization, evaluation, and production deployment**.* Establish standard methodologies for **LLM evaluation, model benchmarking, AI quality measurement, and performance assessment**.* Evaluate emerging AI technologies, foundation models, and third-party solutions to find opportunities for innovation … solutions** at scale.* Deep expertise in **LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures**.* Hands-on experience with **LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment**.* Good foundation in **statistics, probability, optimization, experimentation, and applied machine learning**. ...

MLOps pipelines for model versioning, automated retraining, performance monitoring, and drift detection as cloud usage patterns evolve. Experiment with and apply generative AI and LLM capabilities to FinOps workflows - such as natural language interfaces for cost querying, AI-assisted tagging remediation, or intelligent cost allocation suggestions. Collaborate with FinOps analysts … ecosystem (scikit‐learn, XGBoost, Prophet), experience building and deploying models, and familiarity with MLflow or equivalent MLOps tooling. Generative AI: practical experience with LLM APIs (Azure OpenAI, OpenAI, or equivalent) for building intelligent interfaces or automating classification, tagging, and cost attribution tasks. Software engineering fundamentals: Python, SQL, Git, CI/ ...

like LangChain, LangGraph, LlamaIndex, and Semantic Kernel. Hands-on exposure to both API-based (e.g., Claude, GPT, Gemini) and open-source (e.g., Llama, Mistral) LLM-based solution design. • Agentic AI & Multi-Agent Architecture: Deep expertise designing autonomous and multi-agent systems that reason, plan, and act using tools. Command … with advanced patterns such as GraphRAG and agentic RAG to maximize factual grounding and minimize hallucination in production.• LLMOps, Evaluation & Responsible AI: Experience operationalizing LLM and agentic systems at scale—evaluation harnesses and metrics for quality, groundedness, and safety; observability, tracing, and monitoring (e.g., LangSmith, LangFuse); guardrails and red-teaming ...

evaluation frameworks Hands-on experience building AI/ML applications (RAG, agent frameworks, MCPs, skills, harnesses) and taking them to production or in platforming (LLM or MCP gateway, agentic runtime, auth, data retrieval, eval tooling) Experience running AI systems in production at scale, including observability, cost and capacity planning, regression ...

Python andpython-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow,PyTorch).. Experience working with language models like LLM's APIs andoptimizingtheir usage for specific applications. Experience with the following programming languages: Python, C++, Java, R, SQL Strong written & verbal communication skills and ability ...

delivery of assigned features and components end to end, from technical design through deployment, monitoring, production support, and continuous improvementBuild and enhance large language model application features using retrieval augmented generation, orchestration frameworks, evaluation methods, agentic workflows, and tool integrationContribute to technical designs, participate in design reviews, and identify risks ...

down complex problems, make pragmatic tradeoffs, and ship iteratively, backed by strong communication across product, design, and operations Bonus points for conversational AI or LLM orchestration experience, including speech technologies such as Deepgram, ElevenLabs, Whisper, or OpenAI Realtime Bonus points for working knowledge of cloud telephony or CPaaS platforms such ...

guidanceTranslate technical findings into actionable recommendations for both executive and technical audiencesServe as a subject matter expert on AI and LLM security across the Cato Networks customer baseContribute to development of internal knowledge sharing, solution playbooks, and enablement materials for partners and customersFoster collaboration with our product management, support ...

guidance Translate technical findings into actionable recommendations for both executive and technical audiences Serve as a subject matter expert on AI and LLM security across the Cato Networks customer base Contribute to development of internal knowledge sharing, solution playbooks, and enablement materials for partners and customers Foster collaboration with ...

love to hear from you. Pigment is seeking an experienced GenAI Engineer with a strong CS background and experience with Large Language Models (LLM) to join our innovative and fast-paced team. In this role, you will work on cutting-edge NLP projects and play a crucial part in developing ...

SageMaker, AWS S3, AWS EMR, CI/CDPrior experience in the fraud domain and a strong understanding of fraud detection techniquesExperience designing and deploying LLM-based solutions in productionWe're people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. ...

cloud platforms such as AWS, Azure, or GCP; hands‐off deployment experience is beneficial but not required. Exposure to generative AI application development, including LLM APIs, agentic workflows, retrieval, vector databases, or agent frameworks such as LangChain, LangGraph, or AutoGen. Familiarity with AI‐assisted coding tools such as Claude Code ...

unable to work at home 100% of the time.**Your Role:*** Lead architecture and implementation of GenAI applications using AWS services, especially large language model capabilities such as Amazon Bedrock* Define reusable architecture patterns for model customization, prompt orchestration, retrieval pipelines, and agentic workflows* Design agentic AI systems incorporating tool ...

scale distributed systems Experience implementing and deploying machine learning systems at scale Experience building load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Deep experience operating Kubernetes and cloud infrastructure at scale Experience with AI accelerator platforms (GPUs, TPUs, or emerging hardware ...

high-performance, large-scale distributed systemsExperience implementing and deploying machine learning systems at scaleExperience building load balancing, request routing, or traffic management systemsFamiliarity with LLM inference optimization, batching, and caching strategiesDeep experience operating Kubernetes and cloud infrastructure at scaleExperience with AI accelerator platforms (GPUs, TPUs, or emerging hardware)Representative projectsDesigning ...

large-scale consumer applications Previous experience as a site lead, office lead, or similar multi-team leadership role Background in building infrastructure for LLM training or inference Contributions to open-source infrastructure or AI infrastructure projects Experience scaling teams from 0 to 20+ engineers Active involvement in the London ...

engineers. Experience with AEC, real estate, BIM, geospatial, or digital twin data Experience integrating ML into practitioner‐facing workflows Familiarity with responsible AI practices LLM or GenAI deployment patterns Power BI or other visualization tools Experience with agentic engineering practices Life at Gensler At Gensler, we are as committed ...