MS – Lead Fullstack Engineer – Job9476
Summary
We are seeking a highly skilled and experienced Lead Fullstack Engineer to join our dynamic team. This role is pivotal in driving the development of innovative software solutions that leverage cutting-edge technologies. The ideal candidate will play a crucial role in designing and implementing robust backend systems, developing scalable frontend applications, and utilizing Azure Cloud services for deployment and orchestration. As a leader, you will mentor junior developers and collaborate with cross-functional teams to ensure the delivery of high-quality software solutions that meet our business objectives.
Responsibilities
As the Lead Fullstack Engineer, you will be responsible for:
- Designing and Implementing Backend Systems: Utilize C# /.NET and Python to create robust backend systems that are scalable and maintainable.
- Developing Frontend Applications: Build scalable frontend applications using modern JavaScript frameworks, ensuring a seamless user experience.
- Architecting Microservices: Design and implement microservices architecture to enhance system modularity and scalability.
- CI/CD Pipeline Implementation: Develop and maintain Continuous Integration and Continuous Deployment (CI/CD) pipelines to streamline the software development lifecycle.
- Collaboration: Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software solutions that align with business goals.
- Mentorship: Provide guidance and mentorship to junior developers, fostering a culture of continuous learning and improvement within the team.
- Continuous Improvement: Contribute to the continuous improvement of development practices, ensuring the adoption of best practices and modern technologies.
- AI Systems Development: Design and implement multi-agent AI systems using frameworks like LangChain, AutoGen, and CrewAI, and develop AI-powered decision engines and autonomous task execution systems.
- Event-Driven Architectures: Implement event-driven architectures using message queues such as Azure Service Bus and RabbitMQ to enhance system responsiveness and scalability.
- Data Preparation: Utilize Azure Data Factory to create ETL/ELT pipelines for AI data preparation, ensuring data is ready for analysis and model training.
- Infrastructure Management: Leverage Azure DevOps for CI/CD pipelines and Infrastructure as Code (ARM/Bicep) to manage cloud resources efficiently.
- Workflow Orchestration: Use Azure Logic Apps for complex workflow orchestration and B2B integrations, ensuring seamless data flow across systems.
- Monitoring and Observability: Implement monitoring and observability tools to ensure system reliability and performance.
Requirements
Must-Have Skills
- C# /.NET: Proficiency in C# and .NET framework for backend development, including experience with .NET Core for building scalable applications.
- Python: Strong knowledge of Python for backend services, data processing, and AI-related tasks.
- Microservices Architecture: Experience in designing and implementing microservices architecture, focusing on modularity and scalability.
- JavaScript Frameworks: Proficiency in modern JavaScript frameworks (e.g., React, Angular, Vue.js) for developing responsive and dynamic frontend applications.
- Azure Cloud Services: In-depth knowledge of Azure Cloud services for deployment, orchestration, and management of cloud resources.
- DevOps Practices: Familiarity with DevOps practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing.
- Multi-Agent AI Systems: Experience in designing and implementing multi-agent AI systems using frameworks like LangChain, AutoGen, and CrewAI.
- RAG Pipelines: Ability to build Retrieval-Augmented Generation (RAG) pipelines with vector databases such as Pinecone and Weaviate.
- LLM Fine-Tuning: Experience with fine-tuning large language models (LLMs) and optimizing prompt engineering for improved performance.
- AI-Powered Decision Engines: Knowledge in developing AI-powered decision engines and autonomous task execution systems.
- Event-Driven Architectures: Experience with event-driven architectures using message queues like Azure Service Bus and RabbitMQ.
- Azure Data Factory: Proficiency in using Azure Data Factory for creating ETL/ELT pipelines for AI data preparation.
- Azure DevOps: Experience with Azure DevOps for managing CI/CD pipelines and Infrastructure as Code (ARM/Bicep).
- Azure OpenAI Service: Familiarity with Azure OpenAI Service for GPT integration and custom model deployment.
- Azure Logic Apps: Experience with Azure Logic Apps for complex workflow orchestration and B2B integrations.
- Infrastructure as Code: Strong understanding of Infrastructure as Code principles and tools.
- Monitoring and Observability Tools: Experience with monitoring and observability tools to ensure system reliability and performance.
Nice-to-Have Skills
- Kubernetes and Docker: Familiarity with container orchestration using Kubernetes and containerization with Docker.
- Other Programming Languages: Knowledge of additional programming languages such as Java or SQL.
- Database Management: Experience with various database technologies, including Azure Cosmos DB, PostgreSQL, MySQL, NoSQL, and MongoDB.
- Cloud Platforms: Familiarity with other cloud platforms such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
- Machine Learning Frameworks: Experience with machine learning frameworks such as TensorFlow or Apache Spark.