Position: Middle Automation QA (C#) Engineer 1510 + Welcome bonus
Company: MR Lab
Category: QA Automation
Experience required: 2y
English level: intermediate

Requirements:
2+ years of software development and debugging experience in C#
Experience in API testing
Experience with agile methodologies and continuous integration
Knowledge of industry standard test automation tools and experience developing product test harnesses
Experience building and designing test cases including knowledge of test methodologies
Understanding of web applications
Experience in planning and executing regression tests
English - Intermediate

Responsibilities:
Create unit, functional, regression, and performance tests
Develop, enhance, and maintain automation tests for web services, web applications, desktop applications, and framework libraries
Run tests from Azure DevOps build/release pipelines and test plans
Conduct regular code reviews to ensure that best coding practices are followed
Help identify code coverage gaps and develop quality automation code to fill the gaps

About Our Customer:
The сustomer is a leading provider of vehicle lifecycle solutions, enabling the companies that build, insure, repair, and replace vehicles to power the next generation of transportation. The company delivers advanced mobile, artificial intelligence, and connected car technologies through its platform, connecting a vibrant network of 350+ insurance companies, 24,000+ repair facilities, OEMs, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective set of solutions inform decision-making, enhance productivity, and help clients deliver faster and better experiences for end consumers. 

About Our Project:
The aim of the product is to increase the efficiency of the claim processing lifecycle by processing the claims for insurance carriers “straight through”, without human intervention. This is the first digital AI estimating platform built in the customer’s company and is orchestrated by a service pipeline architecture. This AI-powered claims suite encompasses the customer’s core workflow applications/products and brand-new service functions to provide flexible technology for touchless, guided, and conventional claims processing. The AI-based tool assesses total cost of repair in accordance with insurance carrier rules and engagement guidelines, and intends to eventually replace human decision-driven claims processing as applicable.

The team processes AI information by using an engine that examines the prediction data and understands what the predictions are about. This creates an output that will be sent by the insurance carriers towards the clients. The product takes into account numerous variables, including type of vehicle, type of insurance, etc.

Most of the code is developed as microservices to be distributed inside the Customer’s company and then used by external users.

Project Team:
2 AQAs, 2 Software Developers: sub-team that creates artifacts for the whole project team. Overall project team is about 90 people.

Project Stage:
Under Active Development