1 to 25 of 72 Permanent Microsoft Certified Professional Jobs in England

Lead Agentic AI Engineer to join our team and drive the design, development, and deployment of production‐grade generative AI and agentic solutions using Microsoft technologies. This role is ideal for a technically strong engineer who has hands‐on experience building AI solutions, orchestrating agentic workflows, implementing evaluation frameworks … evaluating multi‐agent AI solutions, agent orchestration patterns, RAG architectures, and enterprise integrations Knowledge of agent communication protocols and interoperability patterns, such as MCP and A2A Ability to balance innovation with practical delivery considerations, including risk, cost, security, and production readiness Confidence contributing to pre‐sales while also being able ...

environment using modern programming and database querying languages Experience with containerization Knowledge of agent-to-agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development J.P. Morgan is a global leader in financial services, providing strategic advice and products ...

processing) and cloud platforms (AWS, Azure or GCP). Hands‐on experience with a range of AI concepts such as LLMs, VLMs, RAG, agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Familiarity with ML frameworks (PyTorch, TensorFlow, etc.) and strong proficiency in Python and data structures and algorithms. ...

processing) and cloud platforms (AWS, Azure or GCP). Hands‐on experience with a range of AI concepts such as LLMs, VLMs, RAG, agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Familiarity with ML frameworks (PyTorch, TensorFlow, etc.) and strong proficiency in Python and data structures and algorithms. ...

processing) and cloud platforms (AWS, Azure or GCP). Hands‐on experience with a range of AI concepts such as LLMs, VLMs, RAG, agents, MCP, computer vision, GraphML, recommendation systems or reinforcement learning. Familiarity with ML frameworks (PyTorch, TensorFlow, etc.) and strong proficiency in Python and data structures and algorithms. ...

Engineering, Computer Science or equivalent; advanced degree preferred. Agentic AI/LLMs: LLM orchestration, prompt engineering, context‐window management and production guardrails; MCP, tool‐augmented agents and RAG at enterprise scale. Enterprise integration: Integrating AI into enterprise systems via APIs and data pipelines, with strong security, data governance and residency ...

audiences. Experience gathering and synthesizing requirements across multiple stakeholder groups and influencing product or platform roadmaps. Familiarity with LLM ecosystems (e.g., prompting, RAG, agents, MCP, fine‐tuning, evaluation) and major AI platforms/APIs. Experience in financial services, asset management, or portfolio analytics is a strong plus. Good‐to‐have ...

tools (e.g. Databricks, NoSQL stores) and AI/ML frameworks (e.g. NLP). LLM integration patterns, RAG pipelines, and agentic AI architectures, including MCP server. Domain experience in Credit Risk, Market Risk, Liquidity or Capital. Experience in defining data strategy for advanced analytical initiatives, including data governance, sourcing, and ethical ...

government or academia. Experience in regulated industries such as insurance, financial services, public sector or national‐scale infrastructure contexts. Familiarity with agentic systems design, MCP/A2A protocols, or inference‐time privacy controls. Familiarity innovating with agentic‐driven workflows and toolsets for both research and prototyping tasks, such as Claude ...

Kubernetes, CI/CD, and major cloud platforms. Expertise in LLMs, prompt engineering, vector DBs, RAG pipelines, and Agentic orchestration frameworks. Agentic/integrations: MCP, Salesforce/SAP/Other. Excellent communication with both technical and executive stakeholders. Mentorship capability and collaborative team‐first mindset. BS/MS/ ...

Demonstrated leadership working with engineers, data scientists, and ML practitioners. Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP) Experience with AWS and infrastructure‐as‐code tools such as Terraform. Experience in multi‐agent orchestration. Familiarity with MLOps practices, including CI/ ...

Demonstrated leadership working with engineers, data scientists, and ML practitioners. Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP). Experience with AWS and infrastructure‐as‐code tools such as Terraform. Experience in multi‐agent orchestration. Familiarity with MLOps practices, including CI/ ...

scale. Responsibilities: Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including ...

developer for complex Conversational AI and CX applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment. Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between ...

yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between the company’s AI products and customer's live infrastructure ...

developer for complex Conversational AI and CX applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, Model Context Protocol (MCP) servers) that drive measurable return on investment. Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" between Google ...

Strong understanding of enterprise software deployment architectures (cloud, on-premises, hybrid, air-gapped) Working knowledge of or experience with modern AI: LLMs, agentic systems, MCP, RAG, fine-tuning, evals, and responsible AI would be a strong differentiator Comfortable discussing API integrations, model inference, data pipelines, and ML operations with technical ...

record of production delivery Able to communicate ideas clearly and build strong relationships globally within the front office Previous experience of agentic design (harnesses), MCP servers, and related AI/ML python libraries Strong analytical, problem-solving, and architectural design skills, with an ability to operate effectively in a front ...

evaluating AI/ML expertise, systems engineering, and coding skills to build an engineering squad. Identify skill gaps in emerging tech (Model Context Protocol (MCP), tool‐calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack. Collaborate with product and engineering to resolve blockers ...

needed. Responsibilities: Serve as a developer for complex AI applications, transitioning from rapid prototypes to production‐grade agentic workflows (e.g., multi‐agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customer’s live infrastructure, including ...

yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including ...

yours. Responsibilities Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including ...

/CD, build systems, artifact repositories, cloud‐native technologies, or software supply chain security; Hands‐on experience with AI Agents, RAG, tool use, MCP/Skills, AI evaluation, or AI observability; Experience with large‐scale distributed systems, globally distributed multi‐region systems, or infrastructure for AI training and inference ...

maintaining human-in-the-loop systems and AI monitoring/observability Strong fundamentals in AI/ML evaluation frameworks Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails In depth understanding of modern software design principles (e,g. microservices, event-driven architectures, domain driven ...

/IAP binding, and defense‐in‐depth enforcement Define the layered guardrail framework applied at every boundary, balancing protection with performance Govern the MCP control plane—registry, gateway, and risk scoring—across all internal and third‐party servers Mandate adopt‐over‐build for productized evaluation and observability stacks Establish FinOps ...