MS - Full Stack Engineer - 145

We are seeking a highly skilled and experienced Sr. Fullstack Engineer to join our dynamic team. This role is pivotal in designing and implementing multi-agent AI systems, developing robust backend services, and creating responsive front-end applications. The ideal candidate will leverage their expertise in C# /.NET and Python, along with modern JavaScript frameworks, to deliver scalable and maintainable solutions. The Sr. Fullstack Engineer will also play a crucial role in utilizing Azure Cloud services for deployment and orchestration, while applying DevOps practices for CI/CD automation. This position offers an exciting opportunity to collaborate with cross-functional teams and mentor junior developers, contributing to the overall success of our innovative projects.

Responsibilities

• Design and Implementation: Lead the design and implementation of multi-agent AI systems, ensuring they are scalable, efficient, and maintainable.
• Backend Development: Develop backend services using C# /.NET and Python, focusing on microservices architecture to enhance modularity and scalability.
• Frontend Development: Create responsive front-end applications using modern JavaScript frameworks, ensuring a seamless user experience.
• Cloud Services: Utilize Azure Cloud services for deployment and orchestration, ensuring high availability and performance of applications.
• DevOps Practices: Apply DevOps practices for CI/CD automation, streamlining the development process and enhancing collaboration between development and operations teams.
• Collaboration: Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality solutions that meet business requirements.
• Mentorship: Mentor junior developers, providing guidance and support to foster their professional growth and enhance team capabilities.
• Workflow Orchestration: Implement complex workflow orchestration and B2B integrations, ensuring smooth data flow and process automation.
• AI Integration: Integrate AI capabilities, including GPT integration and custom model deployment, to enhance application functionality.
• Data Preparation: Utilize Azure Data Factory for ETL/ELT pipelines, preparing data for AI applications and ensuring data integrity and quality.

Requirements

• C# /.NET: Proficient in developing applications using C# and the .NET framework, with a strong understanding of ASP.NET Core, Entity Framework, SignalR, and Minimal APIs.
• Python: Experience in backend development using Python, with knowledge of frameworks such as Django and Flask, and libraries like Pandas, NumPy, and Scikit-learn for data manipulation and analysis.
• JavaScript: Strong skills in modern JavaScript frameworks (e.g., React) for building responsive and interactive front-end applications.
• Microservices Architecture: In-depth understanding of microservices architecture, enabling the development of modular and scalable applications.
• Azure Cloud Services: Experience with Azure Cloud services for application deployment, orchestration, and management.
• DevOps Practices: Familiarity with CI/CD pipelines and Infrastructure as Code (ARM/Bicep) to automate deployment processes and manage infrastructure efficiently.
• Event-Driven Architectures: Knowledge of event-driven architectures using message queues (e.g., Azure Service Bus, RabbitMQ) to facilitate communication between services.
• Complex Workflow Orchestration: Experience in implementing complex workflow orchestration and B2B integrations to streamline business processes.
• Serverless Computing: Understanding of serverless computing and event-driven processing to optimize resource utilization and reduce operational overhead.
• GPT Integration: Experience in integrating GPT models and deploying custom AI models to enhance application capabilities.
• ETL/ELT Pipelines: Proficiency in designing and implementing ETL/ELT pipelines for AI data preparation using Azure Data Factory.

Nice-to-Have Skills

• Machine Learning Frameworks: Familiarity with machine learning frameworks (e.g., TensorFlow) to support AI model development and deployment.
• Containerization with Docker: Experience with containerization technologies like Docker to streamline application deployment and management.
• Infrastructure as Code: Knowledge of Infrastructure as Code practices to automate infrastructure provisioning and management.
• Mentoring and Leadership: Strong mentoring and leadership skills to guide junior developers and foster a collaborative team environment.
• AI Integration: Experience in integrating AI technologies into applications to enhance functionality and user experience.