AI Integration & Data Validation QA Analyst

ChiStats; Maharashtra; On-site; INR 600,000 - 900,000; Full time

Job summary

ChiStats is an award-winning AI-native engineering company building practical AI, data, and cloud-enabled solutions for financial services. We are actively expanding our Wealth Management and Compliance technology portfolio in Maharashtra, India.

We are looking for an AI Integration & Data Validation QA Analyst with 2–3 years of experience to validate the integration between our agentic AI quoting platform and SubmissionLink, ensuring correct data consumption and transformation across source

Qualifications

• 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.

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.

Skills

QA testing

API testing

Data validation

Test case design

Communication skills

Non-deterministic outcome testing

Postman

JSON

Stakeholder communication

Independent work with US stakeholders

Tools

Postman

SQL

JSON

Job description

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

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