26-3102: Senior Consultant – Quality Engineering & GenAI - New York, NY

Navitas is seeking an experienced Senior Consultant – Quality Engineering & GenAI to support complex financial services and Capital Markets technology environments. This role will combine functional testing, test automation, data validation, and Generative AI to ensure the quality, reliability, and performance of enterprise applications and data platforms.

The ideal candidate will have strong hands-on experience with Selenium, Java or Python, SQL, Capital Markets data, and modern GenAI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and AI-powered automation.

The successful candidate will work closely with development, QA, data, and business teams to design comprehensive testing strategies, automate testing processes, validate complex financial data, and identify opportunities to leverage AI to improve quality engineering productivity.

• Perform functional, integration, regression, API, and end-to-end testing for Capital Markets and financial services applications.
• Design, develop, maintain, and execute automated test frameworks using Selenium with Java or Python.
• Develop automated test cases covering application functionality, APIs, data workflows, and end-to-end business processes.
• Validate complex Capital Markets data, including market data, reference data, benchmark data, index calculations, and related financial information.
• Develop and execute SQL queries to validate data accuracy, completeness, consistency, and integrity across databases and data platforms.
• Validate data flowing through ETL pipelines, data services, APIs, and downstream applications.
• Test applications supporting index methodologies, benchmark indices, pricing, market data, reference data, and financial calculations.
• Analyze test results, identify defects, and perform detailed root-cause analysis in collaboration with development and technical teams.
• Develop and maintain automated regression suites to improve test coverage and reduce manual testing efforts.
• Test high-volume, real-time, and performance-sensitive financial applications where applicable.
• Leverage Generative AI and AI-powered tools to improve test case generation, test automation, defect analysis, root-cause investigation, test data creation, and overall Quality Engineering productivity.
• Apply LLMs, RAG, AI agents, and Agentic AI frameworks to practical software testing and automation use cases.
• Design, develop, test, or support AI-powered solutions, intelligent automation workflows, and AI-assisted testing capabilities.
• Apply prompt engineering techniques to improve AI-assisted development, testing, analysis, and automation.
• Evaluate and integrate AI tools into existing Quality Engineering workflows and automation frameworks.
• Explore and implement Model Context Protocol (MCP) and other emerging AI technologies to connect AI systems with testing tools, data sources, APIs, and development environments.
• Collaborate with engineering, development, data, and business stakeholders to understand requirements and translate them into effective test strategies.
• Document test scenarios, automation frameworks, test results, defects, and technical findings.
• Contribute to continuous improvement of Quality Engineering practices, automation frameworks, and AI-enabled testing capabilities.
• Mentor team members and provide technical guidance on automation, data validation, and AI-assisted testing.

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical discipline, or equivalent professional experience.
• 8+ years of software quality engineering, test automation, software development, or related technology experience.
• 6+ years of hands-on experience with Selenium using Java or Python.
• 6+ years of hands-on SQL experience, including complex data validation and database testing.
• Strong experience developing and maintaining automated testing frameworks.
• Experience with functional, regression, API, integration, and end-to-end testing.
• Strong understanding of software testing methodologies, Quality Engineering practices, and SDLC processes.
• 6+ years of experience working with Generative AI and/or Large Language Models (LLMs).
• Hands-on experience using AI-powered tools to improve software testing, automation, defect analysis, or engineering productivity.
• Practical experience with RAG, AI agents, Agentic AI, or AI-powered automation workflows.
• Strong understanding of LLM-based architectures, prompt engineering, and AI application development concepts.
• Experience working with databases, ETL pipelines, APIs, and data services.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent verbal and written communication skills.

• Experience with MCP (Model Context Protocol) and MCP-enabled AI tools.
• Experience developing or supporting RAG applications and retrieval pipelines.
• Experience building or testing AI agents and Agentic AI solutions.
• Experience with AI orchestration frameworks and tools.
• Experience integrating LLMs with enterprise applications, APIs, databases, and testing platforms.
• Experience with Python-based AI/ML frameworks and automation tools.
• Experience with API testing tools such as Postman, REST Assured, or similar technologies.
• Experience with CI/CD tools and automated quality gates.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with performance testing and monitoring tools.
• Experience working in Agile/Scrum environments.