Digitas North America · 2 weeks ago
Lead Quality Assurance Engineer in Test
Boston, MA
Full-time
Hybrid
Senior Level, Lead/Staff
$112K/yr - $172K/yrDigitas North America is a Networked Experience Agency focused on creating magnetic experiences for brands. They are seeking a Lead QA Engineer in Test to lead their QA automation team, modernize efficiencies, and implement best-in-class QA methodologies across complex digital ecosystems.
Marketing & Advertising
Responsibilities
Lead QA automation activities across a range of digital initiatives
Define and evolve QA strategy, frameworks, and tooling
Oversee testing of web applications, APIs, and integrated platforms
Incorporate AI-driven testing approaches to improve coverage, speed, and defect detection
Build and grow automation capability while mentoring engineers across geographically distributed QA teams
Regularly interface with senior leadership and represent automation goals within the context of broader organizational objectives
Provide guidance to automation team members on adopting new tools, improving reliability, and scaling automation coverage
Lead the definition, execution, and maintenance of standardized automation QA processes, methodologies, and reporting
Design and implement robust automation frameworks using modern tools and best practices
Drive QA process improvements using industry best practices and emerging technologies
Stay current on digital technologies, testing trends, and AI-assisted QA techniques to support innovation and client demands
Represent the QA capability in cross-organizational meetings and client-facing discussions
Hire, train, and mentor QA engineers and automation resources
Lead and facilitate automation development across geographically distributed QA teams in fast-paced, agile environments
Qualification
Required
Framework Architecture: Design, implement, and maintain scalable test automation frameworks from scratch using Python or Node.js. (Must demonstrate understanding of Design Patterns, OOP, and modular code structure)
Playwright Expertise: Advanced implementation of Microsoft Playwright for: Robust Cross-browser UI automation (handling flakes, dynamic waits, and authentication states)
Programmatic API Testing: Utilizing Playwright's APIRequestContext or libraries like requests/supertest to build integrated end-to-end workflows (UI + API)
API & Hybrid Testing: Designing tests that bypass UI for setup/teardown using direct API calls (optimizing execution time)
Network Interception: Experience mocking/stubbing network requests to isolate frontend components and test edge cases
CI/CD & DevOps Integration: Ownership of the automation pipeline. Integrating tests into GitLab CI/Azure DevOps/Jenkins, managing Docker containers for execution, and setting up quality gates
Strategy & Leadership: Define the testing strategy (Test Pyramid), deciding when to use API vs. UI testing to maximize ROI and stability
Legacy/Migration Knowledge: Experience with Selenium or Cypress to understand migration paths and architectural differences
Software Design Excellence: Proficient in Python or Node.js with a strong adherence to SOLID principles and Design Patterns (Page Object Model, Factory, Singleton, Strategy) to build maintainable and scalable automation frameworks
Modern Frontend Awareness: Solid understanding of HTML, DOM manipulation, and CSS/XPath selectors. Familiarity with modern JS frameworks (React, Angular, Vue) to understand component lifecycles, shadow DOM, and optimize locator strategies (moving beyond fragile selectors)
Code Quality Standards: Ability to write clean, reusable, and self-documenting code. Experience conducting Code Reviews and enforcing coding standards within the QA team
Concurrency & Parallel Execution: Deep understanding of multi-threading, multiprocessing, and asynchronous programming patterns
For Node.js: Mastery of the Event Loop, non-blocking I/O, Promise.all patterns, and Worker Threads for CPU-intensive tasks
For Python: Experience managing the GIL (Global Interpreter Lock), utilizing asyncio for I/O bound tasks, and multiprocessing for parallel data processing
AI Integration: Experience integrating LLM APIs (OpenAI, Anthropic, Gemini) directly into automation frameworks for tasks like automated root cause analysis of failure logs or 'self-healing' mechanisms for broken UI selectors
Synthetic Data Engineering: Leveraging Generative AI to programmatically create large-scale, diverse, and anonymized datasets (PII-free) to cover complex edge cases and boundary conditions
Testing Non-Deterministic Systems: Strategies for validating probabilistic outputs, including semantic similarity checks (using embeddings/vector distance) rather than exact string matching
Risk & Compliance: Validating guardrails against hallucinations, prompt injection attacks, and bias, ensuring the AI behaves within defined safety boundaries
Understanding of responsible AI principles, governance, and risk management in QA contexts
Automation ROI Analysis: Ability to evaluate 'what to automate' vs. 'what to test manually,' prioritizing flows based on business risk, technical complexity, and maintenance cost (avoiding the 'automating for the sake of automation' trap)
Metric-Driven Improvements: Define and track KPIs such as Flakiness Rate, Cycle Time, and Defect Escape Rate to measure the health of the automation suite and drive continuous improvement
Shift-Left Advocacy: Champion 'Quality Engineering' principles early in the SDLC, participating in architecture reviews and design discussions to ensure features are testable before code is written
Cross-Functional Influence: Collaborate effectively with DevOps, Product, and Backend teams to remove blockers, improve test data availability, and align automation goals with business delivery timelines
Holistic Quality Architecture: Lead the strategy for complex, large-scale platforms, orchestrating not just functional automation but integrating performance, accessibility, and security checks into the continuous delivery pipeline
Solution Engineering: Proven ability to translate ambiguous business requirements into scalable, automated technical solutions that address root operational inefficiencies, going beyond traditional QA scope
Preferred
Accessibility testing (WCAG / Section 508)
Performance testing tools (JMeter, k6, Locust)
Cloud-based test execution and environment orchestration
Experience testing AI-driven or data-heavy platforms
Benefits
Medical coverage
Dental
Vision
Disability
401k
Paid time off
Company
Digitas North America
Digitas North America is the Connected Marketing Agency that provides digital media, and creative development.
Founded in 2006
1001-5000 employees
Funding
Current Stage
Late StageLeadership Team
Megan Jones
Chief Media Officer
Recent News
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