101 to 125 of 677 Observability Jobs in England

scale. Key Responsibilities Build, deploy and maintain machine learning models as APIs, streams, and batch services Partner with Data Scientists to industrialise prototypes into production-ready applications Lead on observability, CI/CD automation, and monitoring for ML workflows Develop cloud-native infrastructure using Docker, Kubernetes, and Terraform Contribute to shared ML tooling and experimentation platforms Ensure best practices in More ❯

data ingestion from diverse and complex sources. Model and optimise data for performance, visibility, and downstream analytics/ML use cases. Champion best practices: CI/CD, TDD, GitOps, observability, schema validation, and data quality. Collaborate with data scientists and ML engineers to deploy production-grade AI/ML systems. Guide clients on data strategy, architecture, and platform modernisation. Mentor More ❯

data ingestion from diverse and complex sources. Model and optimise data for performance, visibility, and downstream analytics/ML use cases. Champion best practices: CI/CD, TDD, GitOps, observability, schema validation, and data quality. Collaborate with data scientists and ML engineers to deploy production-grade AI/ML systems. Guide clients on data strategy, architecture, and platform modernisation. Mentor More ❯

treating pods as first-class citizens in a highly available, BGP-based leaf/spine fabric Lead systems administration on Ubuntu and RHEL systems, tuning OS configurations for performance, observability, and compliance Develop services like DNS-based discovery and egress gateways for smart routing of financial traffic Automate infrastructure using Terraform, Ansible, Git, and CI/CD tooling What we More ❯

cloud and edge environments using Terraform, Helm, and Kubernetes (EKS/OpenShift) Automating deployments via CI/CD tools such as GitHub Actions and Argo CD Managing infrastructure security, observability, and cost-efficiency Collaborating with product, research, and engineering teams — and mentoring others in agentic AI About You You’ll bring experience in both AI development and systems engineering, including More ❯

trends and advancements in cloud computing, AWS services, and distributed systems. Advocate for and implement cloud architecture best practices, including CI/CD pipelines, Infrastructure as Code (IaC), and observability tools. Mentor and guide junior architects and engineers in cloud technologies and distributed systems. Qualifications and Requirements Experience 8+ years in cloud architecture, with a strong focus on AWS. Proven More ❯

in Git, SQL optimisation, and async architecture. Excellent communicator who values clarity, documentation, and collaboration. Nice to Have Experience with Supabase , Kubernetes , Docker , Azure , GitHub Actions , vector databases , or observability tools like Prometheus , Grafana , and Langfuse . What Success Looks Like 3 months: You’ve established your 1:1 rhythm, shipped your first automation workflow, and built a trusted partnership More ❯

frontend technologies such as HTML, CSS, HTMX, React Experience of C# with .NET Web and API development Understanding of git, CI/CD and DevOps practices and experience in Observability/monitoring Any knowledge of Actuarial/Commercial Insurance Some exposure to or interest in Terraform and deployment pipelines in AWS or Azure Awareness of modern software techniques such as More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people leadership and communication skills, able to influence technical and non-technical stakeholders. Comfortable working More ❯

services/message buses and other architectural elements Deploy these applications using features such as containers to cloud leveraging CI/CD to support this process backed with good observability when running these in production Ensure quality through the creation of documentation and use of unit/integration/contract testing with a consideration of security/performance requirements We More ❯

or a related technical role. Strong, hands-on experience with Microsoft Azure, including services such as AKS and IaC tooling like Terraform. Solid understanding of cloud-native monitoring and observability tools Proficiency with infrastructure-as-code practices and tools (Terraform, HashiCorp ecosystem). Good knowledge of containerisation and container security, including Docker and Kubernetes. Relevant Azure certifications or equivalent experience. More ❯

C#, .NET 8.0, Redis, MongoDb, SQL Server, Entity Framework, MassTransit, Mediator Frontend:React, Next.js, TypeScript Infrastructure: Azure, Docker, Kubernetes (AKS), Nginx, RabbitMQ Architecture: Microservices, Event-driven patterns, Clean Architecture Observability and Monitoring: Grafana, Loki, Sentry, PostHog Tooling and Practices: Git, CI/CD pipelines, Agile methodologies What We're Looking For Proven experience leading software delivery within a microservice-based More ❯

workflows Extensive, proven experience in MLOps: owning the end-to-end lifecycle of production models , including designing scalable and reliable deployment strategies (e.g., serverless applications, containerization) and model monitoring, observability and continuous improvement Strong proficiency in designing and utilizing CI/CD pipelines and cloud infrastructure (e.g., AWS, GCP, Azure) to automate and streamline the delivery of data science products More ❯

/Azure Functions, API Management). Implement CI/CD (GitHub Actions/Azure DevOps), Infrastructure as Code (Bicep/Terraform), secrets via Azure Key Vault, private networking. Add observability: tracing/telemetry (OpenTelemetry, LangSmith), metrics, logs, cost and token usage monitoring, alerts. Apply evaluation & QA: regression suites, offline eval sets/golden data, RAG evals (faithfulness, answer relevance, citation More ❯