Quality Engineer Roadmap — QE Center of Excellence

Junior

Black Box Techniques (Fundamentals)

Equivalence Partition

Divide inputs into valid/invalid partitions
One test case per partition

Boundary Value Analysis

Test min, min+1, max-1, max values
Test below/above boundaries

Decision Table

Map conditions to outcomes
Spot missing rules

State Transition

Map valid/invalid transitions
Draw state diagrams

Error Guessing
Use Case Testing
Exploratory Testing

API (Fundamentals)

REST Architecture

HTTP Methods

HTTP Status Codes

Data Formats

Request/Response Structure

Headers, body, query parameters, path parameters

Authentication Basics

API Keys, Bearer tokens (conceptual)

JSON Structure

Objects, arrays, nesting, reading JSON

Common Headers

Content-Type, Authorization, Accept

API Documentation Reading

How to read Swagger/OpenAPI specs

Error Responses

Understanding error payloads

SQL (Fundamentals)

SELECT statement

COUNT keyword

WHERE Clause Operators

AND, OR, IN, BETWEEN, LIKE

Basic Joins Explained

INNER JOIN, LEFT JOIN (visual understanding)

ORDER BY & LIMIT

Sorting and pagination

Aliases

Table and column aliases

NULL Values

Understanding NULL behavior

Aggregate Functions Intro

COUNT, SUM, AVG, MIN, MAX

API Testing (Fundamentals)

Postman

Collections
Requests
Variables

Status Code Validation
Payload & Schema Validation
Header Verification

Software Testing (Fundamentals)

Software Testing Lifecycle

Testing Approaches

Dynamic Testing
Static Testing

Bug Lifecycle
Psychology of Testing

Types of Testing

Regression / Smoke / E2E
Sanity / Ad-hoc
Functional / Integration

Test Case Design
Principles of Testing

Programming (Fundamentals)

OOP Fundamentals

Variables & Constants

Declaration, scope, naming conventions

Operators

Arithmetic, comparison, logical

Functions/Methods

Parameters, return values, reusability

Arrays & Lists

Basic collections

Loops

For, while, foreach (practical examples)

Conditionals

If/else, switch statements

Basic Debugging

Reading error messages, print debugging

AI (Fundamentals)

What is AI

ML vs Deep Learning
What are LLMs
How AI Models are Trained

AI Tools Overview

ChatGPT / Claude / Gemini
GitHub Copilot
AI Testing Tools

AI Limitations

Hallucinations
Bias in AI

Prompt Engineering (Fundamentals)

Anatomy of a Good Prompt

Clear Instructions
Specific Requests
Expected Output Format

Basic Prompt Patterns

Question Prompts
Task Prompts
Role Assignment

Common Mistakes to Avoid

Context Engineering (Fundamentals)

What is Context in AI

Tokens Explained
Context Window Limits

Providing Effective Context

Background Information
Relevant Examples
Constraints and Rules

Intermediate 1-4

API Testing (Intermediate)

Postman

Newman CLI (Local Execution, JS Validations)
Request Chaining & Workflows
Environment & Variable Management
Mock Servers

Negative & Edge Case Testing

Invalid Payloads & Missing Fields
Boundary Values on API Inputs

Schema Validation

JSON Schema Response Validation

Swagger / OpenAPI Validation
Data-Driven & Parameterized Testing
Auth & RBAC
API Monitoring Basics

Accessibility Testing (Intermediate)

WCAG Principles

Perceivable / Operable
Understandable / Robust
Conformance Levels (A / AA / AAA)

Visual Accessibility

Color Contrast Ratios (4.5:1 / 3:1)
Text Alternatives & Alt Text
Focus Indicators

ARIA Testing

Roles, States & Properties
Landmarks & Live Regions

Keyboard Accessibility

Tab Order & Focus Management
Skip Navigation

Screen Reader Testing

VoiceOver (macOS/iOS)
NVDA / JAWS (Windows)

Automated Tools

axe DevTools / Lighthouse
WAVE

Mobile Testing (Intermediate)

Testing Techniques

Interruption (Calls, Notifications, Low Battery)
Localization & Internationalization
Performance (Memory Leaks / CPU Usage)
Network (Throttling / Offline Mode)

Interaction Testing

Gestures (Swipe, Pinch, Long Press)
Deep Linking & Universal Links
Push Notifications
App Permissions & Privacy Prompts

Mobile Cloud & Distribution

TestFlight / Firebase App Distribution
Simulators vs Emulators vs Real Devices

Platforms

Native / Hybrid / Responsive Web
iOS vs Android Differences
Device Fragmentation

Programming - Extension

OOP Hands-On

Abstraction / Encapsulation
Inheritance / Polymorphism

Collections & Data Structures

Lists, Maps, Sets, Arrays

String Manipulation / Regex
File I/O Operations
Exception Handling
Unit Testing Basics

SQL (Intermediate)

Advanced Joins

Right Join
Full-outer Join
Self Join

Aggregations

Subqueries

Constraints

GROUP BY & HAVING

Grouping with conditions

CASE Statements

Conditional logic in queries

UNION / INTERSECT / EXCEPT

Combining result sets

NULL Handling

COALESCE, NULLIF, IS NULL patterns

Date/Time Functions

Date manipulation, formatting

AI Deep Dive

LLM Architecture

Transformers / Token Prediction
Temperature Settings

Model Comparison

GPT vs Claude vs Gemini
Cost Considerations

Hands-on Tools

Copilot / Claude Code
AI Browser Extensions

Prompt Engineering (Intermediate)

Prompt Frameworks

TRICE+ / RACE / CREATE

Advanced Techniques

Few-Shot Prompting
Chain of Thought

QE-Specific Prompts

Test Case Generation
Bug Report Writing
Test Data Creation

Context Engineering (Intermediate)

Context Optimization

Prioritizing Information
Structured Templates

Multi-Turn Conversations

Building on Responses
When to Start Fresh

Context for QE Tasks

Requirements Context
Test Scenarios / Error Logs

Senior 1-2

Software Automation

Automation Strategy

Define what should and should not be automated
Identify the right automation level (UI, API, unit) per scenario
Evaluate and recommend tools based on project needs
Estimate automation effort and maintain coverage metrics

Low Code Tools

Testim — create and maintain AI-assisted scripts using smart locators
Mabl — record, maintain journeys and analyze auto-detected regressions

Selenium / Playwright

Write stable locators that survive UI changes (id, css, xpath, accessibility)
Write scripts covering happy path and edge cases
Refactor and update scripts after UI changes
Apply basic POM structure to organize scripts
Use explicit waits and fix flaky tests caused by timing issues
Catch common exceptions and add meaningful error messages

Test Frameworks (Conceptual Awareness)

TestNG / JUnit / NUnit — suites, annotations, parallel execution
Cucumber — feature files, step definitions and Gherkin scenarios

Automation in the QE Process

Triage failures and distinguish flaky tests from real bugs
Report automation coverage and results to the team
Integrate suites into CI/CD for smoke, sanity and regression runs

Performance Testing (Conceptual)

Core Concepts

Differentiate Load, Stress, Volume, Soak and Scalability testing
Define performance acceptance criteria and SLAs with the team
Recognize common issues such as memory leaks, bottlenecks and timeouts

Test Design and Planning

Identify critical user journeys worth performance testing
Define realistic load patterns based on real usage data
Document entry and exit criteria for performance test runs

Tools

JMeter — execute existing scripts, adjust thread count and interpret reports
BlazeMeter — run cloud-based tests and share results with stakeholders
LoadRunner — interpret results generated by the performance engineering team

Results Analysis

Identify response time degradation and error rate spikes
Distinguish between frontend, backend and network bottlenecks
Correlate results with infrastructure metrics (CPU, memory)
Track performance trends across builds and releases

Collaboration and Process

Coordinate with developers and DevOps to resolve bottlenecks
Advocate for performance testing as part of the definition of done
Raise performance risks early based on architecture and load expectations

Testing Best Practices (Advanced)

Risk-Based Testing

Prioritize coverage using likelihood and impact per feature
Adjust depth and scope based on risk level
Document and communicate risk decisions to stakeholders

Dynamic Test Selection

Select regression tests based on scope of change
Reduce execution time without sacrificing meaningful coverage

Estimations

Break down effort by complexity and risk
Apply algorithmic forecasting for predictable work
Apply probabilistic forecasting for ambiguous features
Communicate estimates with confidence ranges not single numbers

Shift-Left Testing

Involve QE from requirements and design phases
Challenge acceptance criteria before development starts
Identify testability issues early to reduce cost of defects

Continuous Testing

Define quality gates that block pipeline progression on failure
Monitor test results across builds and flag coverage gaps
Balance fast feedback with meaningful test depth

Feature Flags and Progressive Delivery

Validate behavior when features are toggled on and off
Test flag combinations and coordinate scope with canary releases

Observability and Monitoring as Testing

Use logs, traces and metrics to validate system behavior
Correlate production incidents with gaps in test coverage
Treat production monitoring as an extension of the test strategy

Reporting and Metrics

Defect Leakage, Defect-Reopen Rate, Test Coverage, DoR and DoD
Present metrics as quality signals not just numbers

Release Management

Define testing scope, sign-off criteria and go/no-go recommendations
Assess readiness based on metrics, risk and open defects

SQL (Advanced)

Views

Stored Procedures

SQL Injection

Windows Functions

Query Optimization & Execution Plans

Understanding EXPLAIN/ANALYZE to identify slow queries

Indexing Strategies

When and how to use indexes effectively

Transactions & Locking

ACID properties, deadlocks, isolation levels

Database Performance Testing

Identifying bottlenecks, query profiling

Data Integrity Validation

Constraints verification, referential integrity checks

API Testing (Advanced)

API Test Strategy

Defining Coverage Across Endpoints (CRUD, Edge Cases, Security)
Risk-Based API Test Prioritization
Contract Testing Awareness (Pact, Spring Cloud Contract)

API Security Testing

OWASP API Top 10 Awareness
Evaluating Auth Flows (OAuth2, JWT, API Keys)
Injection & Broken Access Control Testing

API Governance & Quality

Reviewing API Documentation for Completeness
Evaluating Versioning & Deprecation Impact
Cross-Team API Dependency Mapping

CI/CD Awareness

Evaluating API Test Results in Pipelines
Identifying Gaps in Automated API Coverage
Collaborating with SDETs on Test Suite Health

Accessibility Testing (Advanced)

Accessibility Test Strategy

Defining Org-Wide Standards (A vs AA targets)
Risk-Based Accessibility Prioritization

CI/CD Awareness

Understanding a11y Gates in Pipelines
Evaluating Automated Scan Results (axe-core, Lighthouse)

Accessibility Auditing

VPAT / ACR Documentation
Third-Party Audit Coordination

Inclusive Design Advocacy

Shift-Left Accessibility
Developer & QA Coaching

Mobile Testing (Advanced)

Mobile Test Strategy

Device Matrix Strategy
Coverage vs Cost Trade-offs
Cloud Device Farms (BrowserStack, Sauce Labs)

Mobile Automation Fluency

Reading & Evaluating Appium / XCUITest / Espresso
Reviewing Automation Coverage Gaps
Collaborating with SDETs on Framework Decisions

Mobile CI/CD Awareness

Understanding Build Pipelines (iOS & Android)
Evaluating Release Readiness

Mobile Performance & Security Evaluation

Interpreting Profiler Results (Instruments / Android Profiler)
Evaluating Certificate Pinning & API Security Posture

AI Mastery

Advanced LLM Concepts

Fine-Tuning vs Prompting
RAG (Retrieval Augmented Gen)
Embeddings & Vector DBs

AI Integration

API Access (OpenAI, Anthropic)
AI in CI/CD Pipelines

AI Governance

Security & Privacy
AI Ethics in Testing

Prompt Engineering (Advanced)

Complex Prompt Design

Multi-Step Task Chains
Self-Reflection Prompts
Validation Prompts

Prompt Patterns Library

Reusable Templates
Version Control for Prompts

Advanced QE Applications

AI-Powered Test Planning
Predictive Quality Metrics

Context Engineering (Advanced)

System Prompt Design

Persona Configuration
Behavioral Rules
Output Formatting

RAG Implementation

Document Retrieval
Knowledge Base Integration

Context for Complex QE

Project Context Management
AI Memory Strategies

Synthetic Data Generation

AI-Generated Test Data

Realistic Data Patterns
Edge Case Generation
Boundary Value Data

Privacy-Safe Data

PII Anonymization
Compliant Test Data

Data Validation

Verifying AI-Generated Data
Quality Checks

Software Quality Assurance Roadmap