276 to 300 of 1,462 Azure Jobs in the City of London

latest tools and methodologies What We’re Looking For Strong background in .NET (C#), SQL Server, SSIS/SSAS, T-SQL Experience of data engineering, ETL/ELT pipelines, Azure services (Data Factory, Synapse, Data Lake) Exposure with React/Angular/TypeScript Knowledge of CI/CD and DevOps practices Proven track record of leading development teams and More ❯

LangChain, LlamaIndex, AutoGen, CrewAI) ● Proven track record designing scalable AI architectures (RAG, Graph RAG, multi-agent systems) ● Experience with vector databases (Pinecone, Weaviate, FAISS) and major cloud platforms (AWS, Azure, GCP) ● Strong foundation in MLOps/LLMOps and Agile delivery ● Excellent leadership, communication, and stakeholder engagement skills ● 10+ years’ experience in AI/ML, including senior solution architecture or More ❯

for security, resilience, and scalability, underpinned by automated testing and continuous improvement. Proficient with CI/CD pipelines, Infrastructure as Code (preferably Terraform), and public cloud technologies including AWS, Azure, or GCP. Why Join You’ll be joining a business that values innovation, collaboration, and technical excellence. This is a chance to work in a high-impact environment where More ❯

or FastAPI Solid understanding of RESTful APIs and database design (SQL/PostgreSQL) Experience with testing frameworks and version control (Git) Familiarity with cloud environments (AWS/GCP/Azure) A collaborative mindset and eagerness to work in a small, agile team If you’re excited by the idea of joining a small, talented team where your work has More ❯

for security, resilience, and scalability, underpinned by automated testing and continuous improvement. Proficient with CI/CD pipelines, Infrastructure as Code (preferably Terraform), and public cloud technologies including AWS, Azure, or GCP. Why Join You’ll be joining a business that values innovation, collaboration, and technical excellence. This is a chance to work in a high-impact environment where More ❯

or FastAPI Solid understanding of RESTful APIs and database design (SQL/PostgreSQL) Experience with testing frameworks and version control (Git) Familiarity with cloud environments (AWS/GCP/Azure) A collaborative mindset and eagerness to work in a small, agile team If you’re excited by the idea of joining a small, talented team where your work has More ❯

years) building production-grade software in financial services, trading or data-intensive domains. Solid grasp of data structures, algorithms and software design . Experience with cloud platforms ( AWS/Azure ), distributed data platforms or data warehouses. Familiarity with quantitative analysis, risk models or front-office systems is advantageous. Proven track record of leading projects or mentoring engineers. A pragmatic More ❯

years) building production-grade software in financial services, trading or data-intensive domains. Solid grasp of data structures, algorithms and software design . Experience with cloud platforms ( AWS/Azure ), distributed data platforms or data warehouses. Familiarity with quantitative analysis, risk models or front-office systems is advantageous. Proven track record of leading projects or mentoring engineers. A pragmatic More ❯

and certifications. Person Specification: * Exposure to the insurance industry. * Experience with traditional data science techniques in Python. * Experience building solutions using generative AI (particularly Gemini). * Experience working with Azure and/or Google Cloud Platform (GCP). * Ability to understand and interpret technical design documents. * Strong communication skills, with the ability to work effectively with diverse stakeholders across More ❯

Highly Valued Advanced degree (Master's/PhD) in Computer Science, Machine Learning, or related discipline Research publications in leading AI/ML conferences Cloud platform experience (AWS, GCP, Azure) with production ML deployment Experience with enterprise-scale data engineering and workflow orchestration tools What Our Client Offers Competitive salary package, comprehensive private healthcare, and exceptional benefits in a More ❯

Highly Valued Advanced degree (Master's/PhD) in Computer Science, Machine Learning, or related discipline Research publications in leading AI/ML conferences Cloud platform experience (AWS, GCP, Azure) with production ML deployment Experience with enterprise-scale data engineering and workflow orchestration tools What Our Client Offers Competitive salary package, comprehensive private healthcare, and exceptional benefits in a More ❯

ITAM, HR, CSM, SPM, HAM/SAM). Strong scripting and integration skills - JavaScript, SQL, API/Web Services . Experience integrating ServiceNow with cloud platforms such as AWS, Azure, or GCP. Proven ability to operate as a Technical Design Authority and influence key stakeholders. Desirable Skills Experience with cloud migration projects. Exposure to GenAI or AI-powered ServiceNow More ❯

platform or developer-focused products. Deep understanding of cloud computing, infrastructure-as-code, DevOps tooling , and data/AI platforms. Hands-on experience with one or more of: AWS, Azure, GCP, Kubernetes, Terraform, Databricks, or Vertex AI . Proven ability to collaborate with engineering and research teams to align platform capabilities with end-user needs. Skilled in stakeholder management More ❯

platform or developer-focused products. Deep understanding of cloud computing, infrastructure-as-code, DevOps tooling , and data/AI platforms. Hands-on experience with one or more of: AWS, Azure, GCP, Kubernetes, Terraform, Databricks, or Vertex AI . Proven ability to collaborate with engineering and research teams to align platform capabilities with end-user needs. Skilled in stakeholder management More ❯

for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/ More ❯

experience) in Computer Science, Software Engineering, or a related field. Brings expertise in enterprise architecture, data governance, and cybersecurity. Lives and breathes modern platforms and practices, think AWS/Azure, DevOps, Terraform, Git. Background coding in HTML, JavaScript, and SQL when needed, but also thinks big picture. Has experience leading teams, managing risk, and delivering under pressure. Knows how More ❯

for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/ More ❯

experience) in Computer Science, Software Engineering, or a related field. Brings expertise in enterprise architecture, data governance, and cybersecurity. Lives and breathes modern platforms and practices, think AWS/Azure, DevOps, Terraform, Git. Background coding in HTML, JavaScript, and SQL when needed, but also thinks big picture. Has experience leading teams, managing risk, and delivering under pressure. Knows how More ❯

on expertise in model development, optimisation, and deployment. Deep understanding of ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is a strong advantage. Strategic thinker with the confidence to lead technically and shape the More ❯

on expertise in model development, optimisation, and deployment. Deep understanding of ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is a strong advantage. Strategic thinker with the confidence to lead technically and shape the More ❯

such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with relational databases and data processing and query engines (Spark, Trino, or similar). Familiarity with monitoring, observability, and alerting systems for production ML (Prometheus, Grafana, Datadog More ❯

such as MLflow, Kubeflow, Vertex AI, SageMaker, or similar model management systems. Practical knowledge of infrastructure as code, CI/CD best practices, and cloud platforms (AWS, GCP, or Azure). Experience with relational databases and data processing and query engines (Spark, Trino, or similar). Familiarity with monitoring, observability, and alerting systems for production ML (Prometheus, Grafana, Datadog More ❯

and practical experience with models used in econometrics or marketing measurement. Experience with agile development methodologies, such as Scrum or Kanban. Preferred Qualifications Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Familiarity with DevOps practices and tools for continuous integration and deployment. Solid understanding of system design principles, scalability, and performance optimization. More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯

an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a passion for platform disciplines. Hands-on experience with cloud platforms (AWS, GCP, or Azure), including large-scale ML infrastructure management. Knowledge of GPU computing for model training and serving. Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD More ❯