Senior Software Engineer in Test

Gen•New York, NY

2d•Hybrid

About The Position

We’re looking for a deeply experienced Senior Software Engineer in Test with fluency in scalable frameworks, advancing service-oriented architecture (SOA) practices, and enabling teams to achieve operational excellence through technical innovation and modern tooling. As AI-powered tools increasingly accelerate code generation, the role of engineering is evolving, shifting focus from writing code to orchestrating, reviewing, and rigorously validating it. In this landscape, software engineers in test serve as a vital line of defense, ensuring that the speed of automation never outpaces the quality and reliability of what we ship. This role is not about producing baseline test automation quickly with an AI tool of your choice. It’s about collaboration, making sound decisions, and setting direction as a technical advisor for scalable automation, software quality, and modern AI adoption. You will leverage AI agents as force multipliers while maintaining a high bar for correctness, maintainability, testability, and operational excellence. Success here depends on engineering judgment—choosing the right solution, not just producing code.

Requirements

8+ years of experience in software engineering with a strong focus on test automation and developer enablement.
Proven expertise in architecting, scaling, and maintaining complex automated test frameworks and pipelines for modern web applications.
Extensive hands-on experience with modern test automation tools such as Playwright, Cypress, Selenium, or similar.
Strong proficiency in TypeScript/JavaScript, with experience building reliable, maintainable, and scalable test frameworks (React experience strongly preferred).
Deep understanding of browser internals, including HTML forms, navigation, accessibility, performance, and rendering behavior.
Experience designing testing strategies that balance unit, integration, and end-to-end coverage.
Comfort working across the full data flow, from REST APIs to rendered UI experiences.
Experience with CI/CD pipelines, automated testing at scale, and infrastructure-as-code.
Hands-on experience with cloud-native environments (AWS preferred) and containerization technologies such as Docker and Kubernetes.
Familiarity with DataDog and/or other telemetry tools to ensure system health and observability in production.
Demonstrates organizational impact through mentoring, technical leadership, and driving adoption of quality and automation best practices.
Hands-on experience with tools like Cursor (or equivalent AI-augmented IDEs) and all modern coding models.
Practical understanding of where AI is strong vs. where it falls short, paired with sound discernment in its application.
Ability to use AI agents to quickly project multiple approaches, compare tradeoffs, and converge on the best solution without shipping “AI-shaped” code.
Proactive problem-solver who identifies issues and opportunities before they become blockers, taking ownership without waiting to be asked
Relentlessly curious — constantly asking "why" and "what if," driven to understand systems deeply rather than accepting surface-level answers
Genuinely passionate about the craft of software engineering, not just the output — the kind of person who gets excited about an elegant solution
Thrives in collaborative environments, elevating teammates through knowledge sharing, constructive code reviews, and open dialogue
Growth-oriented mindset with a demonstrated hunger to learn new technologies, paradigms, and approaches — and to apply them meaningfully
Holds a high quality bar for implementation — writes clean, well-tested, maintainable code and expects the same from the codebase around them
Refuses to normalize technical debt — doesn't walk past bad code; actively advocates for and drives improvements to code health and engineering standards
Self-starter who can operate with ambiguity, break down complex problems independently, and drive initiatives from idea to delivery
Continuously invests in their own development through reading, experimentation, side projects, open-source contributions, or community involvement
Balances pragmatism with rigor — knows when to ship and when to push back, always grounded in what's best for the product and the team

Responsibilities

Architect, build, and own scalable test infrastructure and automation frameworks that support multiple product initiatives and teams.
Lead cross-team quality and test automation initiatives, acting as a subject matter expert in automation, testability, and service-oriented architecture.
Develop automation solutions, including tools, frameworks, pipelines, and tests, to support continuous testing and reliable CI/CD delivery.
Expand automated test coverage across web, API, integration, and service layers using tools such as Playwright or related tooling.
Build and maintain test containers to enable consistent, scalable, and reliable automated testing across development and lower-level environments.
Identify and remediate technical debt in automation frameworks and modernize legacy systems with modern tools and methodologies.
Instrument and monitor features using DataDog and other observability tools to ensure system health, resilience, and safe deployments.
Participate in design and code reviews with an emphasis on testability, architectural clarity, long-term maintainability, and developer experience.
Leverage AI assistants/agents for prototyping, scaffolding, refactoring, and exploratory development, then harden solutions through rigorous validation, edge-case coverage, and reliable execution.
Establish quality goals and metrics to measure effectiveness and drive continuous improvement.
Partner closely with engineering, product, and SRE teams to align automation strategies with organizational goals and delivery priorities.
Mentor and develop engineers through paired programming, documentation, and thoughtful, structured feedback.