Junior - 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 - Junior - AI Integration & Data Validation QA Analyst with 1-2years of experience, who will support testing of integrations between our agentic AI quoting platform and SubmissionLink. The role will validate whether Small Business Owner information is correctly transferred through the data model, consumed by AI agents, and represented in insurance applications and the user interface. The successful candidate should have a solid foundation in functional and API testing, strong attention to detail, and an interest in developing expertise in AI and agentic-system validation. Strong communication

skills

and the confidence to interact directly with US-based stakeholders are mandatory. Primary

Responsibilities

Execute functional, integration, and regression tests for AI-enabled workflows Compare information received from SubmissionLink with data consumed by AI agents Validate whether generated insurance applications and UI screens accurately reflect source information Check API payloads, data mappings, required fields, and system responses Execute predefined positive, negative, and edge-case business scenarios Identify and record defects involving incorrect, missing, or inconsistent information Retest resolved defects and support release regression testing Assist senior QA and Engineering team members with issue investigation Participate in discussions with US-based Product, Engineering, and business stakeholders Clearly communicate test progress, issues, and findings Develop knowledge of agentic AI testing, non-deterministic outcomes, and data-integrity validation

Requirements

Required

Experience

and

Skills

1–2 years of software testing

experience

Understanding of functional, integration, and regression testing Basic API testing

experience

using tools such as Postman Familiarity with JSON, API requests, responses, and structured data Ability to compare data across source payloads, system outputs, and user interfaces

Experience

creating and executing test cases Ability to document defects clearly and provide supporting evidence Basic understanding of Agile software development Strong verbal and written communication

skills

Ability and confidence to work directly with US-based stakeholders Ability to explain test findings and data inconsistencies clearly Strong analytical ability, attention to detail, and willingness to learn Preferred

Experience

Insurance domain experience, particularly in quoting, underwriting, or insurance application workflows Exposure to AI, LLM, chatbot, or agentic AI applications Basic SQL or database-validation

skills

Familiarity with data models and data-mapping concepts Awareness of Model Context Protocol (MCP) Exposure to automated API or regression testing

fields, and system responses Execute predefined positive, negative, and edge-case business scenarios Identify and record defects involving incorrect, missing, or inconsistent information Retest resolved defects and support release regression testing Assist senior QA and Engineering team members with issue investigation Participate in discussions with US-based Product, Engineering, and business stakeholders Clearly communicate test progress, issues, and findings Develop knowledge of agentic AI testing, non-deterministic outcomes, and data-integrity validation

Requirements

Required

Experience

and

Skills

1–2 years of software testing

experience

Understanding of functional, integration, and regression testing Basic API testing

experience

using tools such as Postman Familiarity with JSON, API requests, responses, and structured data Ability to compare data across source payloads, system outputs, and user interfaces

Experience

creating and executing test cases Ability to document defects clearly and provide supporting evidence Basic understanding of Agile software development Strong verbal and written communication

skills

Ability and confidence to work directly with US-based stakeholders Ability to explain test findings and data inconsistencies clearly Strong analytical ability, attention to detail, and willingness to learn Preferred

Experience

Insurance domain experience, particularly in quoting, underwriting, or insurance application workflows Exposure to AI, LLM, chatbot, or agentic AI applications Basic SQL or database-validation

skills

Familiarity with data models and data-mapping concepts Awareness of Model Context Protocol (MCP) Exposure to automated API or regression testing