15 of 15 Amazon EC2 Jobs in the Thames Valley

Python/Perl/Bash Application and network security best practices - SSH/Iptables/TLS Hardware management - Server racking/Storage Required knowledge Containerisation - Docker/Kubernetes AWS - EC2/VPC/RDS/EKS/ECS/S3 Terraform Databases - PostgreSQL/MySQL CI/CD and DevOps Tools/principles Nice to have Experience working in More ❯

a culture of continuous learning and development. Requirements Proven experience as an AWS Platform Engineer, with a strong focus on multi-tenanted platforms. Extensive knowledge of AWS services, including EC2, S3, RDS, Lambda, VPC, IAM, CloudFormation, and more. Strong background in networking, including VPN, DNS, load balancing, and firewall configurations. Demonstrated expertise in security practices, including identity and access More ❯

more Share options Private health insurance Wellbeing days What’s required to be successful in this role? Proven experience with AWS cloud services and architecture design, specifically S3 and EC2 Strong hands-on skills in Infrastructure-as-Code, especially with Terraform. Experience with Ansible for configuration management. Solid understanding of Linux systems - specifically Ubuntu Knowledge of containerisation (Docker, ECS More ❯

to purchase more Share options Private health insurance What's required to be successful in this role? Proven experience with AWS cloud services and architecture design, specifically S3 and EC2 Strong hands-on skills in Infrastructure-as-Code, especially with Terraform. Experience with Ansible for configuration management. Solid understanding of Linux systems - specifically Ubuntu Knowledge of containerisation (Docker, ECS More ❯

premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable of designing and delivering ML Ops solutions across various platforms Desirable Skills Background in DevOps with More ❯

premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable of designing and delivering ML Ops solutions across various platforms Desirable Skills Background in DevOps with More ❯

up Leading infrastructure decisions and influencing strategic technical direction Building robust CI/CD pipelines for mobile and cloud applications Managing the Full AWS Lifecycle Setting up and optimizing EC2 instances, Lambda functions, RDS databases Implementing comprehensive cost management and optimization strategies Managing VPCs, IAM policies, and security configurations across environments Monitoring & Observability Building sophisticated monitoring and alerting systems … initiatives Contributing to technical strategy and innovation roadmap What You'll Bring: Essential Skills: AWS Certified DevOps Engineer (or equivalent hands-on experience) Deep experience across core AWS services: EC2, Lambda, RDS, VPC, IAM, CloudFormation, S3 Proven track record managing complete AWS lifecycle including provisioning, monitoring, cost optimization Strong CI/CD pipeline expertise and containerization (Docker/Kubernetes More ❯

knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design More ❯

knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design More ❯

knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design More ❯

for specific problems. Code Quality: Natural aptitude for good code and software architecture. Work Ethic: Hands-on mentality. Preferred requirements Cloud Computing: Strong experience with AWS services, particularly ECS, EC2, Lambda, and AWS Identity and Access Management (IAM). Governance Understanding: Understanding of governance for cloud-based and AI solutions (e.g., SOC2, ISO 42001, EU AI Act). ML More ❯

domains. Strong proficiency in Python and SQL; experience with R is a plus. Solid understanding of statistical techniques and machine learning algorithms. Experience with cloud platforms and services (AWS, EC2, S3, Redshift, Azure). Familiarity with tools like PowerBI and Excel for stakeholder reporting. Experience in industries with large consumer marketplaces (e.g. programmatic media, travel, financial services) is a More ❯

to adapt our detection strategies and effectively respond to evolving threats. About You Strong understanding of AWS cloud platforms with proficiency in a wide range of AWS services (e.g., EC2, S3, RDS, Lambda, IAM, VPC, CloudFormation). Experience in developing and maintaining detection rules to keep our systems secure. Familiarity with GitOps concepts and CI/CD workflows to … programming languages such as PowerShell, Python, or Go, with a focus on security use cases. Hands-on experience in Cyber Security within an AWS cloud environment, including triaging Amazon GuardDuty findings and analyzing AWS CloudTrail logs. Ideally a bachelor's degree in information technology, computer science, information systems, or a related field is preferred but not essential. Relevant More ❯

clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to the technical strategy and suggest … experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement comprehensive ML Ops solutions Desirable More ❯

clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to the technical strategy and suggest … experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement comprehensive ML Ops solutions Desirable More ❯