Description

Key Responsibilities:
AI Systems and Models Testing

• Design and execute comprehensive test strategies for AI systems and models including prompt engineering output evaluation and biassafety testing
• Develop deep understanding of LLM behaviortokenization embeddings attention mechanisms and inferenceto anticipate failure modes
• Construct effective prompts recognize hallucinations and offtarget outputs and assess quality across accuracy tone coherence and bias dimensions
• Apply evaluation metrics specific to generative AI and establish appropriate thresholds
• Test AI systems integrated with RAG pipelines and knowledge bases validating data quality and retrieval accuracy as they impact model outputs
• Understand vector database mechanics similarity search thresholds embedding drift and test edge cases including nearduplicate documents sparse vs dense embeddings and performance under scale Leverage LangChain and LangGraph frameworks to read code understand chain and graph construction identify failure points and write test harnesses Validate integration points using ClientPs testing tool availability and error handling

Test Strategy and Planning:

• Define and execute comprehensive test strategies for securitization platforms ensuring coverage across functional regression integration and performance testing
• Establish testing standards and best practices that span both traditional QA and AIspecific validation

Test Automation and Framework Development:

• Design build and maintain automated test suites to accelerate release cycles and improve coverage
• Leverage AI and ML tools to enhance test coverage improve efficiency and reduce regression cycles
• Securitization Lifecycle QAValidate endtoend deal workflows including setup structuring processing and distributions
• Ensure data integrity across upstream and downstream systems through reconciliation testing and reporting

Release and Regression Testing:

• Coordinate regression testing for platform releases patches and infrastructure changes
• Ensure stability and backward compatibility particularly during critical processing windows

CrossFunctional Collaboration:

• Partner with developers business analysts and product owners to clarify requirements identify edge cases and ensure testability of new features
• Lead defect triage sessions prioritize issues based on business impact and maintain clear documentation through to closure

Quality Leadership and Reporting:

• Define and monitor key quality indicators including defect density test coverage and automation rates
• Present findings to leadership and recommend improvements Mentor junior QA team members and foster a culture of quality across the team
• Production Support Provide production support during critical processing windows investigate incidents and coordinate root cause analysis and remediation efforts

Qualifications:
Experience:

• 7 years of quality assurance or quality engineering experience with at least 3 years in a lead or senior capacity
• Strong domain knowledge in securitization capital markets or similar asset classes

Technical Skills:

• Handson experience with test automation tools Selenium Robot Framework Playwright or similar
• Proficiency in programming languages including Java and Python with demonstrated framework implementation expertise
• Handson API automation and backend system validation experience
• Proficiency in database query development data validation and reconciliation testing
• Experience with CICD pipelines and DevOps practices Jenkins GitHub or similar

AI and ML Competencies:

• Core understanding of LLM architecture and behavior Handson experience with LangChain andor LangGraph frameworks
• Knowledge of RAG pipelines vector databases and agentic solutions
• Familiarity with Model Context Protocols ClientPs and integration testing
• Understanding of bias safety and redteam testing methodologies for AI systems

Key Skills

Education

Any Gradute