Software Engineer - (.NET & Test Automation)

We are looking for a highly motivated Software Engineer with strong expertise in .NET (C#), Node.js, and Test Automation to join our Software Engineering team supporting enterprise Business Platforms and Wealth & Asset Management initiatives. The ideal candidate will have strong backend development experience, hands-on expertise in automation testing, and experience building scalable enterprise applications. This role also requires exposure to AI-assisted development, CI/CD automation, and modern software engineering practices. Requirements Key Responsibilities Backend & Application Development • Design, develop, and maintain scalable backend applications using .NET (C#) • Build secure, scalable, and high-performance RESTful APIs and microservices using Node.js • Develop and optimize MS SQL Server databases, stored procedures, and complex T-SQL queries • Ensure application performance, reliability, scalability, and high availability • Troubleshoot production issues and provide application support when required • Follow software engineering best practices, coding standards, and secure development principles Automation & Quality Engineering • Design, develop, and maintain end-to-end automation testing frameworks from scratch • Develop automation scripts using tools such as: • Playwright • Cypress • Selenium • Execute automated regression, integration, and functional testing • Improve software quality through automation-first engineering practices • Work closely with development and QA teams to ensure comprehensive test coverage CI/CD & DevOps • Build and maintain CI/CD pipelines for automated build, testing, and deployment • Support release management and deployment automation • Improve engineering efficiency through automation and DevOps best practices • Collaborate with cross-functional teams to ensure smooth software delivery Process Improvement & AI Integration • Review existing engineering workflows and identify opportunities for automation • Leverage AI-powered development tools to improve engineering productivity • Apply Large Language Models (LLMs) and AI technologies where appropriate to automate engineering and data-related processes • Research and evaluate emerging AI tools and modern software engineering practices Required Technical Skills • 5+ years of hands-on experience with .NET (C#) backend development • Strong experience developing scalable applications using Node.js • Expertise in building RESTful APIs and microservices • Strong proficiency in MS SQL Server, database design, query optimization, and T-SQL • Strong experience with automation testing tools such as: • Playwright • Cypress • Selenium • Experience developing automation frameworks from scratch • Strong understanding of software testing methodologies and quality engineering • Hands-on experience with Git, version control, and branching strategies • Strong experience building and maintaining CI/CD pipelines • Experience troubleshooting production issues and improving application performance Nice to Have • Experience with AI-assisted coding tools such as GitHub Copilot, Cursor, Claude Code, or similar • Exposure to LLMs and AI-driven engineering workflows • Experience with cloud platforms (Azure or AWS) • Knowledge of Docker, Kubernetes, or containerized deployments • Experience working with Wealth Management or Asset Management platforms • Understanding of Agile and Scrum methodologies Required Competencies • Strong analytical and problem-solving skills • Excellent debugging and troubleshooting capability • Strong ownership mindset with a focus on delivery and quality • Ability to work independently and collaboratively in Agile teams • Excellent communication and stakeholder management skills • Passion for continuous learning and adopting modern technologies • Ability to work in fast-paced enterprise environments Preferred Domain Experience • Banking • Financial Services • Wealth Management • Asset Management • Enterprise Business Platforms Show more Show less

5+ years of hands-on experience with .NET (C#) backend development. Strong experience developing scalable applications using Node.js. Expertise in building RESTful APIs and microservices. Strong proficiency in MS SQL Server, database design, query optimization, and T-SQL. Strong experience with automation testing tools such as Playwright, Cypress, Selenium. Experience developing automation frameworks from scratch. Strong understanding of software testing methodologies and quality engineering. Hands-on experience with Git, version control, and branching strategies. Strong experience building and maintaining CI/CD pipelines. Experience troubleshooting production issues and improving application performance.

Backend & Application Development: Design, develop, and maintain scalable backend applications using .NET (C#); Build secure, scalable, and high-performance RESTful APIs and microservices using Node.js; Develop and optimize MS SQL Server databases, stored procedures, and complex T-SQL queries; Ensure application performance, reliability, scalability, and high availability; Troubleshoot production issues and provide application support when required; Follow software engineering best practices, coding standards, and secure development principles. Automation & Quality Engineering: Design, develop, and maintain end-to-end automation testing frameworks from scratch; Develop automation scripts using Playwright, Cypress, Selenium; Execute automated regression, integration, and functional testing; Improve software quality through automation-first engineering practices; Work closely with development and QA teams to ensure comprehensive test coverage. CI/CD & DevOps: Build and maintain CI/CD pipelines for automated build, testing, and deployment; Support release management and deployment automation; Improve engineering efficiency through automation and DevOps best practices; Collaborate with cross-functional teams to ensure smooth software delivery. Process Improvement & AI Integration: Review existing engineering workflows and identify opportunities for automation; Leverage AI-powered development tools to improve engineering productivity; Apply Large Language Models (LLMs) and AI technologies where appropriate to automate engineering and data-related processes; Research and evaluate emerging AI tools and modern software engineering practices.