Test Lead AI Validation & Integration - Digital Forms

We are looking for an experienced Test Lead to drive the Quality and Validation strategy for a high-impact solution, in a highly regulated industry, involving AI components and Salesforce integration. In this role, you will own both definition and delivery of the Testing & AI Validation Strategy. You will be responsible for defining how solution outputs are verified for correctness, reliability, and safe operation, bridging the gap between newly developed AI Agents components and the client’s Salesforce environment.

Requirements

What you’ll do

Strategy & Planning:

Own the QA Strategy: Design, plan and dDevelop the comprehensive Testing and AI Validation Strategy, covering FunctionalUnit, E2E, Integration, Regression, and User Acceptance Testing (UAT).

Address NFR and align against standards (e.g. GDPR, HIPAA, HITRUST, etc.)

AI Validation Logic: Define validation plans for AI components, specifically determining what constitutes "correct" output, setting success thresholds, and establishing evaluation methods (including handling hallucinations and grounding rules).

Environment & Data: Create detailed plans for Test Environments (Dev/Test/Prod) and define the Test Data Strategy to ensure sufficient coverage for standard scenarios, edge cases, and ingestion failures.

Execution & Reporting:

Hands-on Testing: Execute functional, regression, exploratory, performance, and load tests.

Integration Coordination: Coordinate "Joint End-to-End Validation" efforts, collaborating with the client team to manage testing of Salesforce integration

Pipeline Integration: Integrate testing activities into the CI/CD pipeline for continuous quality assurance

Process Management: Manage Jira test case structures aligned to user stories and acceptance criteria

Metrics: Provide regular reporting, tracking key QA metrics such as defect ratios

Technical Requirements (must-have):

Fluent English

QA Strategy: Experience defining end-to-end testing strategies for complex solutions

End-to-End Testing: Experience in designing and executing E2E tests for complex, integrated systems using any modern testing technology

AI/ML/LLM Testing Experience: Proven ability to validate AI models

Test Data Management: Experience strategizing and managing test data across multiple environments (Dev/Test/Prod)

Traceability mindset: linking requirements → test cases → evidence → defects → release decisions.

Experience testing NFRs: performance, reliability, auditability, security basics.

Strong understanding of privacy and sensitive data handling in testing (PII/PHI minimization, masking/anonymization)

Hands-on automation experience (at least one strong stack): e.g., Python/Java/JS + frameworks (pytest/JUnit/etc.)