This role will focus on validating data movement, mapping, transformation, and integrity across migration testing and the integration between our agentic AI quoting platform and SubmissionLink. AI agents consume Small Business Owner information provided through SubmissionLink and backed by structured data models to create insurance applications.
The role will verify what data is being used, how it moves through the system, and whether it is correctly validated at each stage, from source payloads and migration outputs through APIs, AI agents, business rules, guardrails, and the user interface. It requires strong API, integration, and data-validation skills, along with practical exposure to agentic testing and validation of AI-generated outputs.
The candidate must have strong communication skills and be capable of working directly with US-based Product, Data Intelligence, Engineering, and business stakeholders.
This role will focus on validating data movement, mapping, transformation, and integrity across migration testing and the integration between our agentic AI quoting platform and SubmissionLink. AI agents consume Small Business Owner information provided through SubmissionLink and backed by structured data models to create insurance applications.
The role will verify what data is being used, how it moves through the system, and whether it is correctly validated at each stage, from source payloads and migration outputs through APIs, AI agents, business rules, guardrails, and the user interface. It requires strong API, integration, and data-validation skills, along with practical exposure to agentic testing and validation of AI-generated outputs.
The candidate must have strong communication skills and be capable of working directly with US-based Product, Data Intelligence, Engineering, and business stakeholders.
Key Responsibilities
Understand what data is being used and map how it moves through each stage of the system pipeline
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Perform data validation during migration testing, including source-to-target comparison, completeness checks, accuracy checks, and transformation validation
Validate SubmissionLink data against expected Small Business Owner information and downstream insurance-application outputs
Verify that AI agents correctly consume, interpret, and apply SubmissionLink data when creating insurance applications
Validate data mapping and transformation across source systems, APIs, AI agents, business rules, guardrails, and the UI
Build or execute validation scripts to check data integrity, completeness, schema conformance, and transformation accuracy across the pipeline
Test agentic workflows and validate AI-agent decisions, tool usage, fallback behavior, exception handling, and human-review handoffs
Define and execute validations for AI-generated outputs, including checks for missing, incorrect, inconsistent, unsupported, fabricated, or policy-violating information
Validate AI outputs against defined business rules, data models, guardrails, expected outcome ranges, and acceptance thresholds
Determine whether issues originate in source data, migration logic, data models, integration layers, AI-agent behavior, guardrails, or front-end presentation
Develop integration and regression tests covering common, negative, edge-case, and AI-output validation scenarios
Work directly with US-based Product, Data Intelligence, Engineering, and business teams
Clearly communicate defects, evidence, quality risks, guardrail gaps, and test findings to stakeholders
Required Experience and Skills
1–3 years of QA experience, with a strong focus on API, integration, data validation, or migration testing
Proven experience validating data integrity, completeness, accuracy, and transformation during migration testing
Ability to understand what data is being used, trace it from source to target, and validate it as it moves through system workflows
Strong experience validating complex data models, API payloads, JSON structures, mappings, and schema transformations across multiple systems
Experience testing AI, LLM, or agentic AI applications, including non-deterministic and rules-driven outcomes
Exposure to agentic testing approaches, including validating AI-agent decisions, tool usage, fallback behavior, and workflow outcomes
Experience defining or validating guardrails, acceptance criteria, and validation checks for AI-generated outputs
Strong API testing experience using tools such as Postman
Ability to create detailed test cases focused on data integrity, mapping, transformation, AI-output validation, and edge-case scenarios
Strong functional, integration, regression, analytical, investigative, and defect-isolation skills
Strong verbal and written communication skills, with the ability to work directly and independently with US-based stakeholders
Ability to explain data-integrity issues, AI behavior, guardrail failures, and non-deterministic outcomes to technical and non-technical stakeholders
Preferred Experience
Insurance domain experience, preferably in commercial insurance, quoting, underwriting, or insurance application workflows
Familiarity with Model Context Protocol (MCP)
Experience validating structured data consumed or generated by AI systems
Understanding of AI evaluation methods, acceptable outcome ranges, hallucination checks, validation thresholds, and guardrail effectiveness
SQL or similar data-querying skills
About ChiStats
IT Services & Consulting40 employeesFounded 2019
ChiStats is a private Indian AI engineering company serving financial-services and other mission-critical industries.
