We are building out a large AI-based anti-fraud platform, which is provided to clients on a SaaS platform. We are expanding due to the success of the product, and the size of the client pipeline.
The aim of the ongoing project is to:
• Create SaaS instances for clients in the cloud, containing a large fraud detection platform;
• Integrate the SaaS instance with our clients' in-house infrastructure, as well as the clients' existing applications and data sources; and
• Harden and productionize the instances
Our project has been winning industry awards, and a large book of business has been built up.
The major duties and responsibilities are:
• Develop and implement automation scripts using Ansible, bash, Python, etc.
• Create, modify and productionize Docker containers
• Log monitoring and aggregation
• Troubleshooting and closely work with L1/L2 support teams
Mandatory skills are:
• Strong experience with any Cloud provider
• Ability to write automation scripts, and troubleshoot
• Experience with Docker, and in creating Dockerfiles
• Monitoring and logs aggregation tools: Grafana, ELK, Prometheus, Zabbix, Nagios
• Scripting and automation on bash/Python/Perl
Nice to have
Nice to have skills
The following will be of benefit:
• Experience with Machine Learning
• Experience with IBM Cloud
• Experience with AWS services: EC2, VPC, Route53, ECS, EKS, Fargate.
• Broad experience in deployment and troubleshooting.
English: C2 Proficient
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