SDET

Job Description

Our client is seeking a SDET to join our client's team to support the testing activities (Automation and Manual) of their in-house Claims Processing Platform.

Key Responsibilities:

• Responsible for analyzing the moderately complex requirements, operational problems, specifications and change requests.
• Produce test plans and test cases to determine presence and scope of potential code defects.
• Monitor accurate and thorough test cases, scripts and data with pre-determined results within specified scheduled dates.
• Perform test execution of all assigned test cases.
• Research and provide technical support on operational/test system defects and propose solutions.
• Analyzes test results to ensure functionality meets requirements and recommends corrective action if necessary.
• Maintains documentation of test results to assist in debugging and modification of software.
• Consults with development engineers in resolution of problems.
• Provides feedback in preparation of technical appraisals of systems, application interfaces and application software.

This position is a contract to permanent opportunity offering a career stability and growth! This position is a hybrid opportunity (1-2x onsite per week in Maryland and/or Wash DC office).

Requirements

• Bachelors degree + 5 years of experience is required (if no degree, 9 years is required)
• 5+ years of experience in software testing and test automation (Manual and Automation)
• Prior experience working within a Healthcare Payor Environment, specifically supporting 835 and 837 testing efforts
• Experience with modern testing frameworks beyond Selenium
• Strong analytical and problem-solving abilities

Required Technical Skills:

• Programming Languages: Python, Java/Selenium, SQL
• Test Automation: Selenium, Playwright, API testing frameworks
• Databases: Oracle and Snowflake
• Jira or similar SDLC tool

Nice to have:

• HIPAA Certification
• FACETS and/or QNXT
• Knowledge of context engineering for AI-driven testing
• Cloud & DevOps: AWS services, Docker, Kubernetes, Git
• CI/CD: CloudBees or Jenkins
• AI/ML Frameworks: AWS Bedrock, LangChain, Pandas, and other popular Machine Learning libraries