1 to 25 of 40 Remote Observability Jobs in the South East

automatically deploy updates and fixes into the production environment. Maintenance, troubleshooting: Perform routine application maintenance to ensure the production environment runs smoothly. Develops maintenance requirements and procedures. Monitoring and Observability: Monitors servers, applications and clusters for failures, system crashes and resource usage, etc using tools like Prometheus, Grafana or Elastic Stack (Elastic Search, Logstash and Kibana). FURTHER DUTIES WILL More ❯

automatically deploy updates and fixes into the production environment. Maintenance, troubleshooting: Perform routine application maintenance to ensure the production environment runs smoothly. Develops maintenance requirements and procedures. Monitoring and Observability: Monitors servers, applications and clusters for failures, system crashes and resource usage, etc using tools like Prometheus, Grafana or Elastic Stack (Elastic Search, Logstash and Kibana). FURTHER DUTIES WILL More ❯

in the team Contribute to solution architecture and strategic technical direction Build, integrate, and maintain REST APIs and backend services Champion best practices in software quality, CI/CD, observability, and DevOps Collaborate with cross-functional teams including Product, QA, and DevOps Optionally take on people management responsibilities for engineers Stay updated with emerging backend and cloud technologies Key Skills More ❯

in the team Contribute to solution architecture and strategic technical direction Build, integrate, and maintain REST APIs and backend services Champion best practices in software quality, CI/CD, observability, and DevOps Collaborate with cross-functional teams including Product, QA, and DevOps Optionally take on people management responsibilities for engineers Stay updated with emerging backend and cloud technologies Key Skills More ❯

Java, Python, or similar). Hands-on experience building and maintaining CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins, or similar). Strong understanding of monitoring, logging, and observability tools (e.g., AppInsights, ELK, Prometheus, Grafana). Solid knowledge of test-driven development and experience embedding TDD in automated delivery workflows. Experience working directly within software development teams to support More ❯

across mission-critical systems. Your mission includes: Architecting and maintaining AWS cloud environments Managing Kubernetes clusters (plus Docker & Helm) Building CI/CD pipelines and automated deployment tools Driving observability with tools like CloudWatch, ELK, and Grafana Mentoring junior engineers and shaping DevOps best practices Ensuring security, compliance, and disaster recovery readiness What You Bring You're a tech-savvy More ❯

with IAM engineering experience across authentication, authorisation, single sign-on, multi-factor authentication, identity lifecycle management, OAuth2.0, OpenID Connect, SAML and policy management Knowledge of Site Reliability Engineering, automation, observability, incident management, resilience, disaster recovery, high availability, documentation IAM engineering experience, authentication, authorisation, single sign-on, multi-factor authentication, user lifecycle management, hands on CI/CD approaches and technologies More ❯

. Lead migration projects and modernisation of legacy systems. Ensure compliance with security and regulatory standards in sensitive industries. Provide senior-level support, troubleshooting, and performance monitoring with modern observability tools. Mentor and support junior engineers, collaborating with global teams. Required: Proven full-stack development expertise Node.js, TypeScript, JavaScript, and C#, .NET. Hands-on experience with cloud platforms (Azure preferred More ❯

real-world problems, particularly in scientific and R&D contexts. Key Responsibilities Design, build, and maintain robust ML pipelines and services using modern engineering practices (CI/CD, testing, observability). Collaborate with cross-functional teams to translate business problems into ML solutions. Develop and deploy models for tasks such as classification, regression, recommendation, and natural language processing. Optimise model More ❯

real-world problems, particularly in scientific and R&D contexts. Key Responsibilities Design, build, and maintain robust ML pipelines and services using modern engineering practices (CI/CD, testing, observability). Collaborate with cross-functional teams to translate business problems into ML solutions. Develop and deploy models for tasks such as classification, regression, recommendation, and natural language processing. Optimise model More ❯

real-world problems, particularly in scientific and R&D contexts. Key Responsibilities Design, build, and maintain robust ML pipelines and services using modern engineering practices (CI/CD, testing, observability). Collaborate with cross-functional teams to translate business problems into ML solutions. Develop and deploy models for tasks such as classification, regression, recommendation, and natural language processing. Optimise model More ❯

real-world problems, particularly in scientific and R&D contexts. Key Responsibilities Design, build, and maintain robust ML pipelines and services using modern engineering practices (CI/CD, testing, observability). Collaborate with cross-functional teams to translate business problems into ML solutions. Develop and deploy models for tasks such as classification, regression, recommendation, and natural language processing. Optimise model More ❯

Familiarity with deploying and scaling ML models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semantic search, or event-driven systems like Kafka Additional Information Were a community here that cares as much about your life outside work as how More ❯

pipelines, monitoring, and infrastructure provisioning. Collaborate with developers and engineers to streamline deployments and workflows. Manage AWS services effectively and efficiently. Promote best practices in Infrastructure as Code (IaC), observability, and DevSecOps. Experience & Skills Required Active SC Clearance – mandatory requirement. Strong hands-on experience with AWS services. Proficiency in Terraform and IaC principles. Solid understanding of CI/CD pipelines More ❯

pipelines, monitoring, and infrastructure provisioning. Collaborate with developers and engineers to streamline deployments and workflows. Manage AWS services effectively and efficiently. Promote best practices in Infrastructure as Code (IaC), observability, and DevSecOps. Experience & Skills Required Active SC Clearance – mandatory requirement. Strong hands-on experience with AWS services. Proficiency in Terraform and IaC principles. Solid understanding of CI/CD pipelines More ❯

pipelines, monitoring, and infrastructure provisioning. Collaborate with developers and engineers to streamline deployments and workflows. Manage AWS services effectively and efficiently. Promote best practices in Infrastructure as Code (IaC), observability, and DevSecOps. Experience & Skills Required Active SC Clearance – mandatory requirement. Strong hands-on experience with AWS services. Proficiency in Terraform and IaC principles. Solid understanding of CI/CD pipelines More ❯

neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data into actionable insights and high-quality training data Scale distributed systems using Kubernetes, Terraform, and orchestration tools such More ❯

neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data into actionable insights and high-quality training data Scale distributed systems using Kubernetes, Terraform, and orchestration tools such More ❯

neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data into actionable insights and high-quality training data Scale distributed systems using Kubernetes, Terraform, and orchestration tools such More ❯

transformation and governance Working closely with Engineering, Analytics, Product, and Pricing teams to ensure priorities are aligned Driving improvements in tooling, infrastructure, and engineering practices (CI/CD, testing, observability) Required Experience Proven experience leading Data Engineering teams Strong technical background (5+ years) in building scalable data platforms Excellent communication and stakeholder management skills Hands-on experience with modern data More ❯

teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship More ❯

growing to meet our business needs. What you'll lead: Shape and evolve the backend technical architecture to support product scale and complexity Identify and drive improvements in performance, observability, and infrastructure Lead the design of domain models aligned with evolving business needs Be a go-to person for backend excellence, and improve code quality Engineering centric requirement definition (user More ❯

Model Deployment: MLOps, scaling, data engineering, and AI ethics awareness. Strategic Mindset: Ability to align technology with business objectives and cost efficiency. Security & Compliance Knowledge: GDPR, API authentication, and observability best practices. Big data processing: Understanding data lakes, warehouses, and tools like Spark, Kafka, and Airflow. ETL Pipelines: Ability to evaluate data ingestion, transformation, and cleaning processes. DevOps & CI/ More ❯

data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What We're Looking More ❯

data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What We're Looking More ❯