About the Role

You will help ensure the quality, accuracy, and usability of an AI-driven platform that automates complex geoscience and subsurface workflows.

This role combines software quality assurance with domain expertise. You will work closely with software engineers, AI engineers, product owners, and geoscience experts to validate application functionality, AI-generated results, workflow automation, and overall user experience.

Success in this role requires both strong analytical skills and the ability to understand how geoscientists perform real-world work. You will help ensure the platform delivers technically correct, reliable, and valuable outcomes for users.

You will support applications in the following domain:

• Geoscience - geology, geophysics, petrophysics, and subsurface modeling

Job Duties

• Develop and execute test plans, test cases, and validation scenarios
• Validate end-to-end workflows across web applications, APIs, AI agents, and supporting services
• Verify the quality and correctness of AI-generated outputs and workflow recommendations
• Work with product owners and domain experts to define expected results and acceptance criteria
• Identify, document, and track defects through resolution
• Validate integrations between applications, services, AI agents, and external data sources
• Participate in requirements reviews and help identify quality risks early in the development process
• Perform functional, regression, integration, and user acceptance testing
• Create and maintain test datasets representative of real geoscience workflows
• Help establish quality standards and testing processes for AI-enabled applications
• Use AI-assisted tools to improve testing, validation, documentation, and productivity

Qualifications

• Bachelor's degree in Geology, Geophysics, Petrophysics, Reservoir Engineering, Computer Science, or related discipline
• 5+ years of experience in quality assurance, software validation, product testing, or geoscience workflows
• Experience testing web-based applications and APIs
• Strong analytical and troubleshooting skills
• Experience creating test plans, test cases, and validation procedures
• Ability to investigate and clearly document defects and unexpected system behavior
• Strong written and verbal communication skills
• Experience using AI-assisted tools to improve productivity and quality-related activities

Preferred

• Experience working in geology, geophysics, petrophysics, interpretation, reservoir characterization, or related subsurface disciplines
• Experience testing AI-powered applications
• Experience validating AI-generated outputs or recommendations
• Experience with Azure DevOps, TestRail, or similar quality management tools
• Experience testing cloud-native applications and distributed systems
• Experience writing SQL queries and validating application data
• Familiarity with agentic AI concepts, LLMs, or workflow automation systems
• Energy industry experience is a strong plus

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs. Depending on education, experience, and skill level, a variety of job opportunities might be available, Principal Software QA, and Technical Advisor QA.

How You Work

You are naturally curious and detail-oriented. You enjoy understanding how users work and identifying situations where software behavior does not match business expectations.

You are comfortable working with engineers and domain experts to determine whether a result is technically correct, operationally useful, and consistent with user expectations. You communicate clearly, raise concerns early, and view quality as a shared responsibility across the team.

You use AI-assisted tools effectively while maintaining independent judgment and validating results before they are accepted.

Why Landmark

We are building an AI-driven platform that automates complex geoscience workflows through intelligent agents and specialized tools.

As a QA Engineer / Geoscience SME, you will play a critical role in ensuring these systems deliver accurate, reliable, and trustworthy results. Your work will directly influence product quality, user confidence, and the successful adoption of AI-powered workflows across the geoscience domain.