The Lead Software Test Engineer ensures the quality of complex software platforms by developing tests, coordinating automation efforts, and embedding quality standards across engineering and architecture teams.
Job Description:
The Lead Software Test Engineer applies advanced knowledge of testing principles, methodologies, and techniques to ensure the quality and reliability of complex, distributed software platforms. Serving as an influential participant in design reviews, this role develops and executes functional, integration, system, load, and performance tests; defines system-wide standards for test automation; and coordinates cross-organizational UAT environments in partnership with integrating teams. This role applies effective influence and collaboration-without formal management authority-across Engineering, Product, Architecture, and SRE to embed quality throughout the software delivery lifecycle.
The Lead STE takes the lead on difficult defect detection and troubleshooting, predicts and documents potential risks and constraints, and leverages AI tooling to drive consistency in test automation across the engineering organization. As engineering teams increasingly rely on AI-generated code, the Lead STE serves as a thought leader in evolving quality practices to meet this shift - defining how TDD requirements, code complexity standards, and test coverage thresholds are embedded directly into AI coding agent configurations, ensuring quality is enforced at the point of generation rather than discovered after the fact.
Primary Duties and Key Responsibilities:
Required Experience, Knowledge, and Skills:
USD 122,700.00 - 204,500.00 per year
Compensation:
Compensation includes a base salary in the range of $122,700.00 - $204,500.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
EOE, including disability/vets
The Lead Software Test Engineer applies advanced knowledge of testing principles, methodologies, and techniques to ensure the quality and reliability of complex, distributed software platforms. Serving as an influential participant in design reviews, this role develops and executes functional, integration, system, load, and performance tests; defines system-wide standards for test automation; and coordinates cross-organizational UAT environments in partnership with integrating teams. This role applies effective influence and collaboration-without formal management authority-across Engineering, Product, Architecture, and SRE to embed quality throughout the software delivery lifecycle.
The Lead STE takes the lead on difficult defect detection and troubleshooting, predicts and documents potential risks and constraints, and leverages AI tooling to drive consistency in test automation across the engineering organization. As engineering teams increasingly rely on AI-generated code, the Lead STE serves as a thought leader in evolving quality practices to meet this shift - defining how TDD requirements, code complexity standards, and test coverage thresholds are embedded directly into AI coding agent configurations, ensuring quality is enforced at the point of generation rather than discovered after the fact.
Primary Duties and Key Responsibilities:
- Governs system-level test case libraries end-to-end: sets coverage standards, identifies gaps, and drives closure with engineering and product teams.
- Defines technical standards and reference implementations for test automation at the API, integration, and system end-to-end layers.
- Coordinates with integrating customers to establish and maintain cross-organization test cases and automation in UAT network of environments.
- Identifies teams with test coverage or automation gaps and embeds to lead remediation - coaching on patterns, driving script development, and verifying quality gate criteria are met before release.
- Drives adoption of quality standards within AI agent configurations across engineering teams, ensuring TDD practices, code complexity standards, and test coverage requirements are codified in team project files rather than applied as post-generation checks. Defines system-wide scenarios for load, stress and soak testing.
- Designs and operates shared test execution infrastructure that enables functional and non-functional test suites to run consistently across CI/CD pipelines, scheduled cadences, and multiple environments - reducing manual effort and accelerating quality feedback loops.
- Partners with SRE to design Game Day scenarios that validate system resilience under failure conditions, translating reliability risks and SLO targets into executable test cases.
Required Experience, Knowledge, and Skills:
- Bachelor's degree in a related discipline and 6 years of experience in a related field, or equivalent combinations such as a master's degree and up to 4 years of experience, or 10 years of experience with no degree.
- Hands-on experience developing test automation with modern frameworks such as Playwright, RestSharp, Pact.NET, and xUnit.
- Hands-on experience creating performance test automation with tools such as JMeter or k6.
- Experience with test management and orchestration (test reporting frameworks, TestContainers, etc.).
- Reviews product requirements and system designs with a testability lens, contributing test strategy input during architecture reviews and driving implementation patterns that support maintainable, scalable automation.
- Skilled at building partnership with Product, Architecture, and Engineering teams both inside and outside of the organization.
- Remains current on test automation tooling and methodologies, recommending and driving adoption of advanced approaches that measurably improve coverage, defect detection, or CI/CD feedback cycle times.
- Demonstrated experience working with AI coding tools (such as Claude, GitHub Copilot, or equivalent) and the ability to define and implement quality guardrails within agent configurations, constitutions, or briefings
USD 122,700.00 - 204,500.00 per year
Compensation:
Compensation includes a base salary in the range of $122,700.00 - $204,500.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
EOE, including disability/vets
Similar Jobs at Cox Enterprises
Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Lead enterprise product operations to standardize product management practices, embed AI-first methodologies, develop playbooks and learning programs, drive adoption of discipline frameworks, and partner cross-functionally to improve product readiness and operational change across Cox Automotive.
Top Skills:
Agentic WorkflowsClaudeLlmsPendoPrompt Engineering
Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Contribute across the full SDLC to design, build, test, deploy, and support cloud-native, service-oriented applications. Implement design patterns, data ingestion and cleansing pipelines, integrate with databases and third parties, collaborate with cross-functional teams, and experiment with AI agents and prompt engineering to enhance product features and delivery.
Top Skills:
.Net.Net 10Ai AgentsAWSC#GitJavaJavaScriptK6New RelicNunitPHPPlaywrightPrompt EngineeringRallyRestsharpSeleniumSplunkStencilTerraformTypescriptXunit
Artificial Intelligence • Automotive • Greentech • Information Technology • Machine Learning • Software • Cybersecurity
Lead discovery and delivery for a defined inventory product area: conduct customer interviews, analyze data, write specs, manage backlog in Rally, engage stakeholders and dealers, collaborate with engineering/UX/architecture, and drive go-to-market and adoption activities.
Top Skills:
Ai ToolsRallySpec-Driven Development (Sdd)
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

