Software Testing Lead

Saarthi; Dadri; On-site; INR 300,000 - 540,000; Full time

Job summary

Dailoqa in Dadri, India, seeks a Test Automation Lead to architect robust testing frameworks for software and AI/ML systems, integrating automated validation into CI/CD pipelines while addressing model accuracy and ethical AI concerns.

You will design scalable frameworks for UI, APIs, and AI endpoints, build GenAI test suites, and collaborate with data scientists to verify fairness, drift, and performance across production pipelines.

Qualifications

• Lead test automation initiatives across software and AI/ML domains.
• Design scalable QA frameworks including UI, API, and model-serving components.
• Implement CI/CD–integrated automated testing and shift-left strategies.

Responsibilities

• Design scalable test automation frameworks for frontend, backend, and AI model endpoints.
• Build GenAI‑specific test suites for prompts, LLM interfaces, and vector search accuracy.
• Develop performance testing strategies for AI pipelines (latency, resources).
• Establish continuous testing pipelines with GitHub Actions, Jenkins, or GitLab CI/CD.
• Collaborate with data scientists to validate AI/ML models for accuracy, fairness, drift mitigation.
• Define KPIs and report quality trends to stakeholders in sprint reviews.
• Promote AI testing tools like LangChain and Great Expectations.

Skills

Automation Leadership

QA Strategy

CI/CD

AI/ML Testing

Quality Metrics

Stakeholder Communication

Tools

Selenium

Playwright

Postman

Python

Java

Job description

Overview

As a Test Automation Lead at Dailoqa, you'll architect and implement robust testing frameworks for both software and AI/ML systems. You'll bridge the gap between traditional QA and AI‑specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance.

Description

Role Overview

As a Test Automation Lead at Dailoqa, you'll architect and implement robust testing frameworks for both software and AI/ML systems. You'll bridge the gap between traditional QA and AI‑specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance.

Key Responsibilities

Test Automation Strategy & Framework Design

• Design and implement scalable test automation frameworks forfrontend (UI/UX),backend APIs, andAI/ML model‑serving endpointsusing tools like Selenium, Playwright, Postman, or custom Python/Java solutions.
• BuildGenAI‑specific test suitesfor validating prompt outputs, LLM‑based chat interfaces, RAG systems, and vector search accuracy.
• Developperformance testing strategiesfor AI pipelines (e.g., model inference latency, resource utilization).

Continuous Testing & CI/CD Integration

• Establish and maintaincontinuous testing pipelinesintegrated with GitHub Actions, Jenkins, or GitLab CI/CD.
• Implementshift‑left testingby embedding automated checks into development workflows (e.g., unit tests, contract testing).

AI/ML Model Validation

• Collaborate with data scientists to test AI/ML models foraccuracy,fairness,stability, andbias mitigationusing tools like TensorFlow Model Analysis or MLflow.
• Validatemodel driftand retraining pipelines to ensure consistent performance in production.

Quality Metrics & Reporting

• Define and track KPIs.
• Test coverage(code, data, scenarios)
• Defect leakage rate
• Automation ROI(time saved vs. maintenance effort)
• Model accuracy thresholds
• Report risks and quality trends to stakeholders in sprint reviews.
• Drive adoption of AI‑specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation).

Soft Skills

• Strong problem‑solving skills for balancing speed and quality in fast‑paced AI development.
• Ability to communicate technical risks to non‑technical stakeholders.
• Collaborative mindset to work with cross‑functional teams (data scientists, ML engineers, DevOps). behavior validation