AI Integration & Data Validation QA Analyst

ChiStats is an award-winning, AI-native engineering company focused on building practical AI, data, and cloud-enabled solutions for financial services and other mission-critical industries. We are actively building our Wealth Management and Compliance technology portfolio, including ComplianceAssist — an AI-enabled compliance product initially designed for AMCs regulated by SEBI, with identified potential to extend to AIFs and PMS firms. We are looking for - AI Integration & Data Validation QA Analyst with 2-3 years of

experience

who will will focus on validating 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 candidate must have strong communication

skills

and be capable of working directly with US-based Product, Data Intelligence, Engineering, and business stakeholders. Primary

Responsibilities

Validate SubmissionLink data against expected Small Business Owner information Verify that AI agents correctly consume and apply SubmissionLink data when creating insurance applications Validate data mapping and transformation across source systems, APIs, AI agents, and the UI Test agentic workflows while accounting for acceptable variations in AI-generated outcomes Identify missing, incorrect, inconsistent, unsupported, or fabricated information Validate AI outputs against defined business rules, data models, and expected outcome ranges Determine whether issues originate in source data, the data model, integration layer, AI-agent behaviour, or front end Develop integration and regression tests covering common, negative, and edge-case business scenarios Validate fallback behaviour, exception handling, and human-review

requirements

Work directly with US-based Product, Data Intelligence, Engineering, and business teams Clearly communicate defects, evidence, quality risks, and test findings to stakeholders

Requirements

Required

Experience

and

Skills

2–3 years of QA experience, with a strong focus on API, integration, or data testing Strong

experience

validating complex data models across multiple systems Ability to trace data from the source through APIs, AI workflows, and the user interface

Experience

testing non-deterministic, probabilistic, or rules-driven outcomes Strong API testing

experience

using tools such as Postman Working knowledge of JSON, structured data, and API payload validation Ability to create detailed test cases focused on data integrity, mapping, and transformation Strong functional and regression testing

experience

Strong analytical, investigative, and defect-isolation

skills

Strong verbal and written communication

skills

Ability to work directly and independently with US-based stakeholders Ability to explain AI behavior, data-integrity issues, 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

Experience

testing AI, LLM, or agentic AI applications Familiarity with Model Context Protocol (MCP)

Experience

validating structured data consumed or generated by AI systems Understanding of AI evaluation methods, acceptable outcome ranges, and validation thresholds SQL or similar data-querying skills

strong communication

skills

and be capable of working directly with US-based Product, Data Intelligence, Engineering, and business stakeholders. Primary

Responsibilities

Validate SubmissionLink data against expected Small Business Owner information Verify that AI agents correctly consume and apply SubmissionLink data when creating insurance applications Validate data mapping and transformation across source systems, APIs, AI agents, and the UI Test agentic workflows while accounting for acceptable variations in AI-generated outcomes Identify missing, incorrect, inconsistent, unsupported, or fabricated information Validate AI outputs against defined business rules, data models, and expected outcome ranges Determine whether issues originate in source data, the data model, integration layer, AI-agent behaviour, or front end Develop integration and regression tests covering common, negative, and edge-case business scenarios Validate fallback behaviour, exception handling, and human-review

requirements

Work directly with US-based Product, Data Intelligence, Engineering, and business teams Clearly communicate defects, evidence, quality risks, and test findings to stakeholders

Requirements

Required

Experience

and

Skills

2–3 years of QA experience, with a strong focus on API, integration, or data testing Strong

experience

validating complex data models across multiple systems Ability to trace data from the source through APIs, AI workflows, and the user interface

Experience

testing non-deterministic, probabilistic, or rules-driven outcomes Strong API testing

experience

using tools such as Postman Working knowledge of JSON, structured data, and API payload validation Ability to create detailed test cases focused on data integrity, mapping