1 to 25 of 87 Autonomous Agent Jobs in England

automation, and user experience. Key Responsibilities AI-Driven Architecture: Design and implement RAG pipelines that enhance platform intelligence and content retrieval Agentic AI Integration: Develop and fine-tune autonomous agents for workflow automation, intelligent decisioning, and user engagement Domain Modelling: Leverage understanding of CRM workflows and finance/savings data models to inform product features Data Strategy: Work More ❯

profile will lead to further improved organisational efficiency across PS. Identify, design, and implement AI solutions, with the main focus in Generative AI, e.g. LLMs and AI-driven autonomous Agents, to streamline business processes and significantly reduce manual effort. Automate repetitive and complex tasks using AI solutions, enabling teams to concentrate on high-value strategic activities. Leverage advanced … AI technologies and autonomous agents to solve complex business challenges and drive innovation across PS. Enhance data-driven decision-making through AI, e.g. by developing robust LLMs and intelligent agents capable … of generating actionable insights from large and complex datasets. Collaborate closely with data scientists, analysts, and developers within Roche to ensure seamless integration and successful deployment of GenAI and agent-based technologies. Continuously refine and optimise AI models and autonomous agents to meet evolving business needs and Roche's quality standards. Actively contribute to the PS Data More ❯

systems. In this role, you'll work closely with ML scientists, data engineers, and product teams to help bring innovative solutions-such as retrieval-augmented generation (RAG) systems, multi-agent architectures , and AI agent workflows -into production. As a Senior Machine Learning Engineer, you'll play a key role in developing and integrating cutting-edge AI solutions-including … fast-moving environment where your contributions will directly shape both the future of our platform and your own growth. Key Responsibilities Design, build, and deploy RAG systems , including multi-agent and AI agent-based architectures for production use cases. Contribute to model development processes including fine-tuning, parameter-efficient training (e.g., LoRA, PEFT), and distillation . Build evaluation … and ability to work across disciplines with ML scientists, engineers, and stakeholders. Preferred Qualifications PhD in Computer Science, Machine Learning, Engineering , or a related technical discipline. Experience with multi-agent RAG systems or AI agents coordinating workflows for advanced information retrieval. Familiarity with prompt engineering and building evaluation pipelines for generative models. Exposure to Snowflake or similar cloud data More ❯

systems. In this role, you’ll work closely with ML scientists, data engineers, and product teams to help bring innovative solutions—such as retrieval-augmented generation (RAG) systems, multi-agent architectures , and AI agent workflows —into production. As a Senior Machine Learning Engineer, you’ll play a key role in developing and integrating cutting-edge AI solutions—including … fast-moving environment where your contributions will directly shape both the future of our platform and your own growth. Key Responsibilities Design, build, and deploy RAG systems, including multi-agent and AI agent-based architectures for production use cases. Contribute to model development processes including fine-tuning, parameter-efficient training (e.g., LoRA, PEFT), and distillation. Build evaluation pipelines … and ability to work across disciplines with ML scientists, engineers, and stakeholders. Preferred Qualifications PhD in Computer Science, Machine Learning, Engineering, or a related technical discipline. Experience with multi-agent RAG systems or AI agents coordinating workflows for advanced information retrieval. Familiarity with prompt engineering and building evaluation pipelines for generative models. Exposure to Snowflake or similar cloud data More ❯

profile will lead to further improved organisational efficiency across PS. Identify, design, and implement AI solutions, with the main focus in Generative AI, e.g. LLMs and AI-driven autonomous Agents, to streamline business processes and significantly reduce manual effort. Automate repetitive and complex tasks using AI solutions, enabling teams to concentrate on high-value strategic activities. Leverage advanced … AI technologies and autonomous agents to solve complex business challenges and drive innovation across PS. Enhance data-driven decision-making through AI, e.g. by developing robust LLMs and intelligent agents capable … of generating actionable insights from large and complex datasets. Collaborate closely with data scientists, analysts, and developers within Roche to ensure seamless integration and successful deployment of GenAI and agent-based technologies. Continuously refine and optimise AI models and autonomous agents to meet evolving business needs and Roche's quality standards. Actively contribute to the PS Data More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

of AI/ML algorithms, data science, and machine learning is essential. 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, focusing on prompt engineering and LLMs. Writing production-grade Python applications. Managing version More ❯

/ML algorithms, data science, and 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 More ❯

AI/ML algorithms, data science, 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. More ❯

/ML algorithms, data science, and 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 More ❯

AI/ML algorithms, data science, 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. More ❯

operate autonomously across diverse data sources and workflows. Implement scalable data processing pipelines using Apache Spark and Python. Build, train, and fine-tune advanced AI/ML models for agent reasoning, planning, and execution. Integrate solutions with MCP (Massively Concurrent Processing) servers or equivalent architectures. Work closely with data engineers, researchers, and platform teams to ensure robust deployment. Continuously … research and integrate emerging techniques in agent-based AI, multi-agent systems, and reinforcement learning. Required Skills & Experience: 4+ years of experience in AI/ML engineering or data-intensive systems. Strong proficiency in Python for AI, ML, and data engineering tasks. Deep experience with Apache Spark (PySpark or Scala-based implementations). Solid understanding and hands-on … with libraries such as TensorFlow, PyTorch, LangChain, or Ray is a plus. Ability to write clean, efficient, and well-documented code in a collaborative environment. Desirable: Experience with multi-agent coordination or LLM-based autonomous agents. Background in distributed systems, knowledge graphs, or real-time data processing. Contributions to open-source AI projects or relevant research publications. More ❯

Social network you want to login/join with: Power Platform and Copilot Agent Architect, slough col-narrow-left Client: Capgemini Location: slough, United Kingdom Job Category: Other - EU work permit required: Yes col-narrow-right Job Views: 4 Posted: 10.06.2025 Expiry Date: 25.07.2025 col-wide Job Description: Power Platform and Copilot Agent Architect Get The Future You … more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

more sustainable, more inclusive world. Your Role Capgemini is looking for Microsoft Power Platform and Copilot Architect with hands-on experience in creating enterprise grade Power Platform applications, autonomous agents, AI assistants and Generative AI solutions using Microsoft cloud. This role will collaborate with our strategic customers to help them envision, plan and design innovative solutions to connect … solutions using Microsoft Copilot Studio that integrate with Microsoft 365, Azure, and enterprise systems. Application Development : Architect, design, and develop scalable enterprise applications using Microsoft Power Platform and Azure. Agent Development & Customization: Create and configure custom Copilot agents tailored to specific business needs. Extend Copilot capabilities using plugins, APIs, and enterprise data connectors. Customer Engagement : Understand customer requirements and More ❯

that powers advanced generative and agentic AI systems. You'll play a critical role in enabling fast-paced prototyping and deployment of intelligent applications—supporting workflows across LLMs, autonomous agents, semantic search, RAG pipelines, and memory-augmented reasoning systems. Key Responsibilities: Design and build scalable, secure data pipelines using Google Cloud Platform (GCP) services including BigQuery, Dataflow, Cloud … and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and observability. Optimize data workflows for performance, cost-efficiency, and latency. Maintain strong data governance … alongside ML or AI teams in a research-heavy, experimentation-focused environment A detail-oriented, systems-thinking approach to infrastructure and data modelling Nice to Have: Experience with multi-agent architectures or autonomous agents Understanding of responsible AI practices, including prompt injection prevention and data privacy Experience with Google Vertex AI, Amazon Bedrock, or Azure AI Studio More ❯

that powers advanced generative and agentic AI systems. You'll play a critical role in enabling fast-paced prototyping and deployment of intelligent applications—supporting workflows across LLMs, autonomous agents, semantic search, RAG pipelines, and memory-augmented reasoning systems. Key Responsibilities: Design and build scalable, secure data pipelines using Google Cloud Platform (GCP) services including BigQuery, Dataflow, Cloud … and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and observability. Optimize data workflows for performance, cost-efficiency, and latency. Maintain strong data governance … alongside ML or AI teams in a research-heavy, experimentation-focused environment A detail-oriented, systems-thinking approach to infrastructure and data modelling Nice to Have: Experience with multi-agent architectures or autonomous agents Understanding of responsible AI practices, including prompt injection prevention and data privacy Experience with Google Vertex AI, Amazon Bedrock, or Azure AI Studio More ❯

that powers advanced generative and agentic AI systems. You'll play a critical role in enabling fast-paced prototyping and deployment of intelligent applications—supporting workflows across LLMs, autonomous agents, semantic search, RAG pipelines, and memory-augmented reasoning systems. Key Responsibilities: Design and build scalable, secure data pipelines using Google Cloud Platform (GCP) services including BigQuery, Dataflow, Cloud … and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and observability. Optimize data workflows for performance, cost-efficiency, and latency. Maintain strong data governance … alongside ML or AI teams in a research-heavy, experimentation-focused environment A detail-oriented, systems-thinking approach to infrastructure and data modelling Nice to Have: Experience with multi-agent architectures or autonomous agents Understanding of responsible AI practices, including prompt injection prevention and data privacy Experience with Google Vertex AI, Amazon Bedrock, or Azure AI Studio More ❯

that powers advanced generative and agentic AI systems. You'll play a critical role in enabling fast-paced prototyping and deployment of intelligent applications—supporting workflows across LLMs, autonomous agents, semantic search, RAG pipelines, and memory-augmented reasoning systems. Key Responsibilities: Design and build scalable, secure data pipelines using Google Cloud Platform (GCP) services including BigQuery, Dataflow, Cloud … and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and observability. Optimize data workflows for performance, cost-efficiency, and latency. Maintain strong data governance … alongside ML or AI teams in a research-heavy, experimentation-focused environment A detail-oriented, systems-thinking approach to infrastructure and data modelling Nice to Have: Experience with multi-agent architectures or autonomous agents Understanding of responsible AI practices, including prompt injection prevention and data privacy Experience with Google Vertex AI, Amazon Bedrock, or Azure AI Studio More ❯

that powers advanced generative and agentic AI systems. You'll play a critical role in enabling fast-paced prototyping and deployment of intelligent applications—supporting workflows across LLMs, autonomous agents, semantic search, RAG pipelines, and memory-augmented reasoning systems. Key Responsibilities: Design and build scalable, secure data pipelines using Google Cloud Platform (GCP) services including BigQuery, Dataflow, Cloud … and vector database integrations. Implement retrieval-augmented generation (RAG) systems using tools like Pinecone, FAISS, Chroma, or PostgreSQL. Develop infrastructure to support short- and long-term memory in autonomous agents. Work with AI orchestration frameworks (LangChain, LangGraph, CrewAI) to ensure reliable data integration and observability. Optimize data workflows for performance, cost-efficiency, and latency. Maintain strong data governance … alongside ML or AI teams in a research-heavy, experimentation-focused environment A detail-oriented, systems-thinking approach to infrastructure and data modelling Nice to Have: Experience with multi-agent architectures or autonomous agents Understanding of responsible AI practices, including prompt injection prevention and data privacy Experience with Google Vertex AI, Amazon Bedrock, or Azure AI Studio More ❯

in Python, experienced in building multi-step intelligent systems, and comfortable working across UI, APIs, cloud AI platforms, and observability tools. Responsibilities Rapidly build and iterate on LLM- and agent-based prototypes for various use cases, including chatbots, copilots, and A2A task agents. Implement agentic workflows, multi-step reasoning pipelines, and memory management using frameworks such as LangChain, CrewAI … to implement applications that adhere to responsible AI guidelines. Optimize model performance for latency, throughput, and cost-efficiency. Implement short-term and long-term memory modules to support persistent agent behaviours. Use cloud platforms such as Amazon Bedrock, Google Vertex AI, and Azure AI Studio for model orchestration and deployment. Build and integrate UI prototypes using tools like React … in Python programming. Experience in building multi-step intelligent systems. Knowledge of machine learning and artificial intelligence. Familiarity with frameworks like LangChain and CrewAI. Additional Skills & Qualifications Experience with agent collaboration (A2A) or multi-agent task routing systems. Familiarity with MCP tools or advanced model configuration systems. Understanding of prompt injection prevention, ethical AI, and safety frameworks. Background More ❯