15 of 15 Semantic Kernel Jobs in the UK

into campaign performance and ROI• Build and deploy AI automations leveraging LLMs and AI agent frameworks: Design and implement solutions using cutting-edge technologies like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, and similar frameworks to automate tasks, enhance decision-making, and improve campaign performance• Stay ahead of the curve on emerging AI technologies: Continuously research and … real-world marketing challenges• Experience building products and automations leveraging Large Language Models (LLMs) and AI agent frameworks• Familiarity and practical experience with tools like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar• Demonstrated ability to identify innovative AI solutions and successfully scale them within an organization• Strong coding skills in Python or similar languages, with More ❯

into campaign performance and ROI• Build and deploy AI automations leveraging LLMs and AI agent frameworks: Design and implement solutions using cutting-edge technologies like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, and similar frameworks to automate tasks, enhance decision-making, and improve campaign performance• Stay ahead of the curve on emerging AI technologies: Continuously research and … real-world marketing challenges• Experience building products and automations leveraging Large Language Models (LLMs) and AI agent frameworks• Familiarity and practical experience with tools like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar• Demonstrated ability to identify innovative AI solutions and successfully scale them within an organization• Strong coding skills in Python or similar languages, with More ❯

practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data … love you to have: Experience in AI/ML engineering or applied machine learning. Proven experience delivering production-grade AI solutions. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

architectures and solutions. Resolve technical blockers and objections, collaborating with engineering to share insights and improve products. Maintain deep expertise in AI Foundry & App architecture (Agentic AI framework, Semantic Kernel, Foundry SDK, Responsible AI) and App architecture/cloud native dev (APIs, containerization, microservices, event-driven, Python, Java or .NET). Maintain and grow expertise in … design/modernization and cloud native development (e.g., APIs, containerization, microservices, event-driven, Python, Java, .NET). Expertise in AI & ML models (e.g., Agentic AI framework, AI Foundry, Semantic Kernel, Foundry SDK, Responsible AI, fine-tuning/inferencing, etc.). Proven ability to lead technical engagements (e.g., hackathons, PoCs, MVPs) that drive production-scale outcomes. Microsoft More ❯

ecosystem. The ideal candidate will bring hands-on expertise in designing and building AI-driven solutions using Azure-native tools and frameworks such as Azure OpenAI, Prompt Flow, Semantic Kernel, Azure AI SDKs (including azure-ai-projects, azure-ai-inference), and open-source frameworks like LangChain. Familiarity with traditional Azure AI services (e.g. Document Intelligence, Vision More ❯

Experience with cloud-native applications on Azure and deployment of Python applications on Azure. AI Frameworks and Tools: Familiarity with frameworks and tools such as LangChain, LlamaIndex, CrewAI, Semantic Kernel, Autogen and Agno. An understanding of how Large Language Models (LLMs) work. Data Engineering & Modelling: Understanding of ORM/entity relationships, NoSQL, JSON, XML, SQL and More ❯

and machine learning. Demonstrated proficiency in: Rapid prototyping of Data Science and Machine learning problems on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, with a focus on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with More ❯

machine learning principles. Demonstrated proficiency in: Rapid prototyping of data science and machine learning solutions on large datasets. Building agentic workflows and autonomous agents using frameworks like Langchain, Semantic Kernel, AutoGen, and LangGraph. Developing and optimizing generative AI models, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version control with Git and More ❯

love you to have: Experience in AI/ML engineering or applied machine learning. Proven experience delivering production-grade AI solutions. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong understanding of data More ❯

to deliver real-world results What We’re Looking For • 5+ years' ML experience with strong Python skills • Experience with NLP, LLMs, and prompt engineering • Familiarity with LangChain, Semantic Kernel, or AutoGen • OCR/document layout modelling experience • Cloud-native deployment experience (AWS, Azure, or GCP) • Strong engineering mindset – writing production-grade, scalable code Bonus Points More ❯

science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g., Semantic Kernel, Langchain, and Agentic frameworks). Experience deploying models into production using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong More ❯

science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g. Semantic Kernel, Langchain and Agentic frameworks). Experience deploying models into production using APIs, containers, or cloud-native services. Familiarity with Azure and infrastructure-as-code tools. Strong More ❯

uplift capability. Technical Expertise: Hands-on experience applying Generative AI in real-world business settings. Skills in prompt engineering, RAG, guardrail design, orchestration, and tools like LangGraph or Semantic Kernel. Deep knowledge of ML model development, deployment, and evaluation. Proficiency in Python, PyTorch, TensorFlow, SQL, Spark, and AWS tools like SageMaker and Bedrock. Understanding of scalable data infrastructure More ❯

Visual Studio environment and embracing AI-assisted development. Comfortable working independently on AI-related features in a remote-first, async-friendly environment. Nice to Have: Experience with LangChain, Semantic Kernel , or similar orchestration frameworks. Familiarity with embedding models , vector stores, or retrieval-augmented generation (RAG). Contributions to open-source AI/dev tools or participation More ❯