Position: DevOps Engineer
Company: KaaIoT Technologies, LLC
Category: DevOps
Experience required: 3y
English level: intermediate
Published: 2021-07-01T00:00:00+03:00

**Requirements:**
3+ years in DevOps and software development
Experience with AWS services (EC2, S3, VPC, KMS, Route53, ECR, IAM, RDS, Lambda, Cognito)
Experience with Terraform
Experience with Ansible
Experience with Jenkins
Experience with Prometheus/Grafana, Cadvisor, Node Exporter
Scripting skills in Python
Knowledge of Java build automation tools (MVN, Grandle)
Familiarity with common development tools like Git
Understanding CI/CD principals
Good written and verbal communication skills in English

**Would be a plus:**
Experience with AWS (CloudTrail, CloudWatch, SES, SQS, X-Ray)
Experience with Prometheus/Grafana, Cadvisor, Node Exporter
Experience with DynamoDB, PostgreSQL, Snowflake, MYSQL
Experience with Elasticsearch, Filebeat, Kibana
Experience with CrowdStrike Falcon
Experience with NGINX
Knowledge of Kafka, Zookeeper

**Responsibilities:**
Automate deployment of application infrastructure
Manage CI/CD processes
Support of existing infrastructure
Extend monitoring
Migration of existing architecture to a new environment

**About the project:**
The pioneering medical technology company delivering technology into the growing global dialysis market, reimagining dialysis for patients and healthcare providers. The company developed the mobile haemodialysis system for the treatment of patients with renal failure. It is also the first-of-its-kind system to receive approval from the FDA in April 2020 for use in patients at their home. The haemodialysis systems are widely used by patients all over the US. In May 2020 in collaboration with the US Department of Health and Human Services the company delivered 50 haemodialysis systems to the US hospitals.

**The main area of the project:**
Real-time monitoring and analytics of the device and patient data;
Over-the-air software updates;
Cloud-based monitoring and reporting;
Reporting and data visualization.

**Problem:**
Traditional hemodialysis is a time-consuming routine which requires dedicated hospital facilities and staff. As a result, it is difficult to scale up for a larger number of patients as well as to be implemented in remote or poverty areas. Today, a lack of such specialized medical facilities around the world results in the statistics that only 10% of those who need dialysis actually receive it.

**Solution:**
We developed a digital platform that enables real-time monitoring and analytics of the device and patient data and allows medical staff to monitor and adjust the treatment process remotely. The device contains numerous sensors, actuators, and controllers, which were enabled with remote access capabilities. The collected information is presented to medical staff in real-time web dashboards, which allow doctors to view patient treatment analytics over time.
The platform is designed to be scalable, with the ability to monitor several thousand customer treatments in parallel. To do this, we employ Cloud-based technology and algorithms that automatically identify and report problems. And the platform meets the requirements for end-to-end security, which makes it HIPAA compliant. The platform allows the staff to automate documentation and streamlines machine management with two-way wireless data transfer and cloud-based monitoring and reporting. Treatment data is stored in the device, downloadable from wherever you are or integrated with your EMR. Also, two-way data communication can automatically send treatment data to the cloud.
Our team responsible for the entire engineering cycle, from the initial device’s software design to ground-up implementation, testing automation, analytics, and UI production rollout.

**Overall project technology stack:**
AWS services (EC2, S3, VPC, KMS, Route53, ECR, IAM, RDS, Lambda, Cognito), Terraform, Ansible, Jenkins, Prometheus, Grafana, Cadvisor, Node Exporter, Python, MVN, Grandle, Snowflake, NGINX, Kafka, Zookeeper.