Software Development Engineer in Test (QA Automation) - Search Lane

About AlphaSense

The world's most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients' own research content. Our platform is trusted by over 4,000 enterprise customers, including a majority of the S&P 500.

Founded in 2011, AlphaSense is headquartered in New York City with over 1,300 people across the globe and offices in the U.S., U.K., Finland, India, and Singapore. For more information, please visit www.alpha-sense.com.

The Role

We are seeking a highly skilled Software Development Engineer in Test (SDET) to join our dynamic engineering Search lane.

The ideal candidate is a versatile engineer who is well-versed in both software development and quality assurance practices. You will play a crucial role in ensuring the quality of our product by embedding quality ownership within the team. Your expertise in automation, cloud services, Kubernetes, and modern programming languages will be instrumental in driving our testing strategy and delivering high-quality software. You will collaborate closely with developers, product managers, and other stakeholders to identify test requirements and contribute to the overall quality strategy and product development.

Requirements

Proficiency in Programming Languages: Extensive experience in languages such as Java, Kotlin, C#, Python, or JavaScript
Debugging and Troubleshooting: Advanced analytical and problem-solving skills for identifying, diagnosing, and resolving complex issues
Automated Testing Tools: Deep expertise in using and optimizing automated testing tools and frameworks like Selenium, TestNG, JUnit, or similar
Test Automation Frameworks: Proven experience in designing and scaling test automation frameworks for complex applications.
Continuous Integration/Continuous Deployment (CI/CD): Advanced familiarity with CI/CD tools (ArgoCD preferably). including integrating test automation into CI/CD pipelines
Cloud Platforms: Experience with public clouds and Kubernetes
API Testing: Extensive experience with API testing tools and techniques (e.g., Postman, REST-assured) and creating comprehensive API test strategies

Software Development Lifecycle: In-depth understanding of the software development lifecycle (SDLC) and agile methodologies, with a focus on implementing and improving quality assurance processes. Proven experience in engaging developers into a quality process is a plus
Communication Skills: Excellent communication skills to effectively guide and collaborate with team members and stakeholders.

Key Responsibilities

Lead efforts in troubleshooting complex issues (diving into developers code if required) and provide high-level analysis of test results to inform product improvements
Design, develop, and maintain quality automation (unit, component, integration) and frameworks for various types of testing including functional, regression, and performance
Enable engineers to ship code reliably and faster, helping them and guiding if needed with the best QA practices
Continuously improve and streamline a testing process, tools, and methodologies. Coach engineers on automation best practices and support automation backlog efforts
Perform manual testing as needed to complement automated tests
Analyze test results and provide actionable feedback to improve software quality
Participate in code reviews and contribute to best practices for testing and quality assurance
 Enabling Developer Ownership of Quality and Test Automation, guiding them on integration of these practices effectively within their development workflows
Collaborate with developers in reviewing unit test and integration results for coverage analysis.

Bonus points if you have...

Performance Testing: Strong knowledge and hands-on experience with performance testing and tools like k6 or JMeter.
Machine Learning and AI: Experience in testing machine learning or AI-driven applications.
Technical Degree: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Domain Knowledge: Having experience in the Search Domain would be a huge plus, along with working with Solr, ElasticSearch or any Search Engine.