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
Who we're looking for?
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 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.