Senior Software Engineer

Key Responsibilities:

1. Design, develop, and maintain backend systems using .NET Framework and .NET Core (C#, Web API, MVC) for enterprise-grade applications.

2. Develop, integrate, and consume secure and efficient RESTful APIs.

3. Collaborate on AI feature integration, such as implementing machine learning models, using AI frameworks or APIs, and optimizing inference workflows.

4. Work with SQL Server and other relational databases for data modeling, complex queries, and performance tuning.

5. Support UI integration using AngularJS and Angular; contribute to responsive and interactive web components.

6. Participate in the full software development lifecycle including requirements gathering, design, coding, testing, deployment, and support.

7. Create and maintain comprehensive technical documentation, including AI model usage and API endpoints.

8. Engage in Agile practices: attend stand-ups, contribute to sprint planning, reviews, and retrospectives.

9. Identify and resolve application issues and production bugs.

Propose improvements for system architecture, performance, and security.

Qualifications:

1. Minimum 3+ years of hands-on experience in backend development using .NET technologies (C#, Web API, MVC).

2. Solid working knowledge of AngularJS and Angular for frontend integration.

3. Proficiency in JavaScript, HTML, CSS, and jQuery for UI tasks.

4. Strong grasp of Object-Oriented Programming (OOP), design patterns, and service-oriented architecture (SOA).

5. Practical knowledge or experience in AI/ML conceptsthis includes working with AI models, APIs (e.g., OpenAI, TensorFlow, Azure Cognitive Services), or machine learning workflows.

6. Experience with SQL Server, including complex queries, stored procedures, and optimization techniques.

7. Familiarity with Agile development methodologies and version control systems like Git.

8. Strong analytical, problem-solving, and debugging skills.

9. Excellent communication skills and a collaborative mindset.

10. Self-driven, adaptable, and capable of managing tasks in a dynamic environment.

Preferred (Nice to Have):

Experience integrating AI models into production environments.

Exposure to Python or other AI-related scripting languages.

Familiarity with cloud platforms (e.g., Azure, AWS) and deploying AI/ML services.

Understanding of data preprocessing, model training, and evaluation basics.