Lead Software Engineer

Role: Lead Software Engineer

External Title: Lead Software Engineer

Internal Title: Senior Software Engineer

Job Description

If you are skilled at building software applications, have expertise in modern frontend technologies, cloud-native development, AI-assisted software engineering, and enjoy developing creative solutions to complex problems, then we want to hear from you!

We are looking for a highly motivated Lead Software Engineer who will lead the development of scalable, secure, and high-performing enterprise applications. This role requires strong expertise in Angular (Primary), React (Secondary), Python (Primary Backend), and .NET Core (Secondary Backend), along with experience in modern software engineering practices, cloud technologies, technical leadership, and AI-driven development using GitHub Copilot and Coding Agents.

Responsibilities

- Design, develop, and deploy end-to-end software solutions using the latest SPA (Single Page Application) and Micro-Frontend frameworks, while driving engineering strategy and technical excellence across teams.
- The selected resource will be responsible for end-to-end web application development for the Applications/Tools team, including Frontend, Middle Tier, and Backend implementations, with a strong preference and leadership focus on Frontend development.
- Develop modern, scalable, responsive, and reusable user interfaces using Angular (Primary) and React (Secondary).
- Design and develop secure, scalable APIs, microservices, and backend services using Python (Primary) and .NET Core (Secondary).
- Should have expertise in writing unit tests, implementing automated testing strategies, and working with SQL Server as the backend repository.
- Leverage GitHub Copilot, GitHub Copilot Chat, GitHub Copilot Coding Agents, and AI-assisted development workflows within Visual Studio Code to improve engineering productivity, code quality, test coverage, and delivery velocity.
- Design, build, and maintain reusable Copilot Skills, Prompt Libraries, Agent Workflows, MCP (Model Context Protocol) integrations, Developer Accelerators, Templates, and Engineering Assets to improve consistency and scalability across teams.
- Drive adoption of AI-Driven Application Development Lifecycle (AIDLC) practices including requirements generation, architecture design, code generation, automated testing, code reviews, documentation generation, and application modernization initiatives.
- Work collaboratively in Agile Scrum teams including Developers, Senior Developers, Architects, Tech Leads, Product Owners, Scrum Masters, and QA/Automation Engineers. This may require one to two hours of overlap with global teams in the US (PST) based on project needs.




- Collaborate with QA Engineers and Product Owners to ensure quality is built into the product from requirements through deployment.
- Ensure products and features are designed to perform, scale, and operate reliably under load.
- Ensure technical decisions support organizational goals related to quality, scalability, reliability, maintainability, security, and performance.
- Take accountability for code quality assurance, architecture reviews, design direction, code review readiness, and technical debt identification and reduction.
- Promote collaboration, innovation, engineering best practices, and adoption of up-to-date web development techniques.
- Practice TDD ensuring code is covered by unit and integration tests while continuously improving testability.
- Identify project risks proactively and work with leadership to define and execute mitigation plans.
- Participate in on-call support activities whenever required.
- Demonstrate strong knowledge of Software Development Life Cycle (SDLC) methodologies and Agile delivery practices.
- Work closely with Product Management teams to translate business requirements into technical solutions.
- Troubleshoot, diagnose, and resolve application issues while communicating progress, blockers, and status effectively.
- Delegate work and assignments to team members and mentor junior engineers on technology, domain knowledge, coding standards, AI-assisted development practices, and performance optimization techniques.
- Foster a culture of continuous learning, engineering excellence, ownership, accountability, and responsible AI adoption.
- Evaluate and adopt emerging AI-powered developer tools and technologies while ensuring governance, security, compliance, and engineering quality standards.
- Willingness to work in a fast-paced, highly collaborative, and energetic environment with distributed teams is a must.

Qualification Requirements

B. Tech/BE in Computer Science, MCA, or related field.

Highly proficient with 6 9 years of hands-on experience in the following:

Frontend Technologies

Strong working experience with Angular (Primary), React. js, JavaScript, TypeScript, HTML5, CSS3, SCSS, Micro-Frontend Architecture, Responsive Web Design, and modern frontend development practices.

Strong understanding of frontend architecture patterns, state management, performance optimization, accessibility, and reusable component development.





Experience building scalable enterprise-grade front-end applications with a focus on maintainability, performance, and user experience.

Backend Technologies

Strong hands-on experience with Python (Primary) using FastAPI, Flask, Django, REST APIs, Microservices, and distributed application development.

Working experience with Microsoft development stack including C#, ASP.NET MVC, Web API, .NET Core, SQL Server, SQL Azure, and Microservices architecture.

Experience designing and developing RESTful APIs and scalable enterprise applications.

Experience implementing secure authentication and authorization mechanisms using industry-standard protocols and frameworks.

Database Technologies

Strong experience with SQL Server, SQL Azure, database design, query optimization, and performance tuning.

Good knowledge of XML and JSON.

Experience working with large-scale datasets and performance-sensitive applications.

Software Engineering

Hands-on experience with Object-Oriented Design and Software Engineering principles.

Good working knowledge of enterprise architectural patterns and design patterns.

Strong understanding of secure coding practices and application performance optimization.

Good exposure to Unit Testing frameworks using MSTest, NUnit, and xUnit.

Knowledge of Test Automation frameworks is a plus.

Strong experience using GitHub Copilot, GitHub Copilot Chat, GitHub Copilot Coding Agents, and AI-assisted software development tools within Visual Studio Code or similar development environments.

Experience creating and maintaining Copilot Skills, Prompt Libraries, MCP Integrations, AI Agent Workflows, Developer Accelerators, Templates, and reusable engineering assets.

Proven experience leveraging AI-assisted development for code generation, code reviews, documentation generation, modernization initiatives, automated testing, refactoring, and productivity improvements.

Strong understanding of AI governance, responsible AI practices, validation of AI-generated code, and enterprise AI adoption strategies.

Experience implementing AI-Driven Application Development Lifecycle (AIDLC) practices across planning, development, testing, deployment, and support activities.

Cloud DevOps

Strong experience with Azure DevOps, including source control, CI/CD pipelines, automated deployments, release management, and integration of QA automation into deployment pipelines.

Experience with cloud-native application development and deploying applications to Microsoft Azure.

Knowledge of containerization technologies such as Docker and Kubernetes (AKS) is preferred.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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