10 of 10 Observability Jobs in West End of London

Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Leadership: A track record of leading complex projects. Problem solving: Strong analytical problem-solving skills and attention to detail. You have the ability to More ❯

application or platform Proficient in Python programming language Proficient knowledge of software applications and technical processes within a given technical discipline (e.g., Cloud, artificial intelligence, Android, etc.) Experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, and others Experience with continuous integration and More ❯

programming language. Cloud-native technologies: Experience in deploying to cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Curiosity: A hunger to learn and grow your skills. Problem solving: Strong analytical problem-solving skills and attention to detail. You have the ability More ❯

core systems, focusing on scalability, performance, and reliability. Write clean, maintainable code and contribute actively to the codebase. Define and uphold engineering best practices (code quality, CI/CD, observability, etc.). Collaborate closely with the CTO and product team to align technical delivery with strategic goals. Continuously improve team operations, development workflows, and developer experience. Play a key role More ❯

and delivering solutions. Job Responsibilities Develop and maintain RESTful APIs and microservice architectures Deliver software solutions to address non functional requirements in applications and systems Design, develop, and implement observability solutions Automate tooling, techniques and processes Participate in collaborative development projects Evolves and debug critical components of applications and platforms. Contributes to JPMorgan Chase's site reliability community via internal More ❯

project or initiative. Extensive experience of working with Kubernetes and Cloud Platforms (AWS, GCP or Azure). Expertise in one or more of the following areas: Database Administration, Networking, Observability Tools, or automation of infrastructure. Ability to tackle design and functionality problems independently with little to no oversight. Excellent debugging and trouble shooting skills. Preferred qualifications, capabilities, and skills Experience More ❯

/finance. Certification in AWS, Kubernetes (CKE) and Terraform Familiar with databases (SQL or NoSQL). Experience with client/server software architectures & networking, or microservice architectures. Experience with observability tools like Grafana, Prometheus, Open Telemetry and others. Experience with streaming architectures and tools (e.g. Kafka) About Us J.P. Morgan is a global leader in financial services, providing strategic advice More ❯

infrastructure using cloud-native tools Work closely with ML scientists, data engineers, and product managers to align on requirements and delivery timelines Drive engineering quality, CI/CD integration, observability, and unit testing for AI-enabled software components Mentor junior engineers and uphold engineering excellence across the team Required Qualifications, Capabilities, and Skills: Master's degree in computer science, Software More ❯

Job Description Are you ready to apply Make sure you understand all the responsibilities and tasks associated with this role before proceeding. Join a dynamic team where we prioritize efficient, high-quality software development. Our fully implemented CI/CD More ❯

role PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics Track record of developing, deploying business critical machine learning models Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc Experience monitoring, maintaining, enhancing existing models over an extended time period Specialism in NLP or Computer Vision Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with More ❯