1 to 25 of 31 High Availability Jobs in the East of England

/SNS, Kinesis Streams/Firehose, and Kafka Connect. Establish integration standards, best practices, reusable frameworks, and governance models. Design solutions that ensure high availability, scalability, observability, and security. Evaluate system integration options and recommend optimal patterns (Pub/Sub, CQRS, event sourcing, streaming analytics, request-response APIs … Experience designing event-driven and microservices architectures. Strong knowledge of: API integration patterns (REST, GraphQL) ETL/ELT and data pipelines Distributed system design High throughput and low-latency data streaming Good understanding of Java/Python/Node.js for integration logic. Familiarity with containerization & orchestration (Docker, Kubernetes). ...

000pa Bedford, Hybrid Permanent, Full Time Can you Design, implement, and maintain robust, secure, and scalable network infrastructure solutions? Are you able to ensure high availability, performance, and security of bpha's network systems while mentoring junior staff and collaborating across IT teams? Then we want to hear … standards. Implement and manage network security measures (firewalls, VPNs, IDS/IPS). Configure and maintain routers, switches, wireless systems, and firewalls. Deploy scalable, high-performance network solutions with minimal downtime. Conduct regular network maintenance, updates, and upgrades. Perform security audits and vulnerability assessments. Respond to and mitigate network ...

000pa Bedford, Hybrid Permanent, Full Time Can you Design, implement, and maintain robust, secure, and scalable network infrastructure solutions? Are you able to ensure high availability, performance, and security of bpha's network systems while mentoring junior staff and collaborating across IT teams? Then we want to hear … standards. Implement and manage network security measures (firewalls, VPNs, IDS/IPS). Configure and maintain routers, switches, wireless systems, and firewalls. Deploy scalable, high-performance network solutions with minimal downtime. Conduct regular network maintenance, updates, and upgrades. Perform security audits and vulnerability assessments. Respond to and mitigate network ...

manage backend applications on AWS using services such as EC2, S3, Lambda, and RDS. Implement containerization using Docker and orchestrate deployments with Kubernetes. Ensure high availability, scalability, and reliability of backend systems. Set up, maintain, and optimize CI/CD pipelines using Jenkins for automated testing and deployments. ...

optimizing data pipelines and ensuring smooth data flow across the organization. The role bridges data engineering, operations, and DevOps practices to deliver reliable, high quality, and timely data for analytics, reporting, and business applications. Your Responsibilities 1. Data Pipeline Development & Maintenance Design, build, and maintain automated, scalable data pipelines … pipelines meet SLAs, quality standards, and security guidelines 2. Data Platform Operations Manage and monitor data platform operations using DataOps/DevOps practices Ensure high availability and reliability of data platforms (cloud or on prem) Troubleshoot pipeline failures and perform root cause analysis (RCA) 3. Automation & CI/ ...

ability to operate effectively within an agile, service-oriented team. This role involves contributing to platform stability, implementing continuous improvements, and ensuring reliable, high-quality support for enterprise-scale Azure infrastructure while collaborating closely with senior team members and stakeholders. The Responsibilities Perform root cause analysis, investigation, diagnosis … reporting of cloud-related issues. Monitor and optimize Azure environments to ensure high availability, performance, and security. Troubleshoot and resolve build, deployment, and infrastructure issues. Ensure compliance with industry standards and best practices for security, scalability, and reliability. Create and maintain detailed documentation for processes, configurations, and procedures. ...

optimisation. Key Responsibilities Design, deploy and manage cloud infrastructure within Microsoft Azure Automate infrastructure and operational processes using scripting and PowerShell Monitor system performance, availability and security across cloud environments Configure infrastructure to support reliable application deployment Troubleshoot cloud infrastructure issues and perform root cause analysis Ensure cloud environments … troubleshooting cloud infrastructure Desirable Experience Azure certifications such as Azure Administrator Knowledge of identity and access management and cloud security best practices Experience supporting high availability and disaster recovery environments Degree in Computer Science, Engineering or equivalent experience Contract Details Initial 6 month contract Outside IR35 Hybrid working ...

experienced Software Engineer to support a range of large-scale, business-critical platforms. You'll join a collaborative engineering team working on high-availability systems used across the UK, contributing to new feature development, platform enhancements, and ongoing operational performance. About the Role You will work as part ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

Network Engineer to be responsible for the design, implementation, management, and optimisation of customer network environments, with a strong focus on network security and high availability. The ideal candidate will bring hands-on experience with Palo Alto, Cisco, and WatchGuard technologies, and ideally have a strong understanding of networking ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments to evaluate model efficacy … . . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high-volume data processing and real-time streaming architectures. Strong understanding of recommendation system design and personalisation algorithms. Familiarity with Generative AI and its applications ...

seeking .NET Developer to work out of their plush offices in the heart of Hertford, Hertfordshire. You will be working on the development of high-availability and highly-transactional .NET/C# applications which will be critical to the launch of their new online music shopping channel. ...