MS - Lead Fullstack Engineer
Listed on 2026-02-12
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Software Development
Cloud Engineer - Software, Software Engineer, DevOps, AI Engineer
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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.
ResponsibilitiesAs the Lead Fullstack Engineer, you will be responsible for:
- Designing and Implementing Backend Systems
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Utilize C# /.NET and Python to create robust backend systems that are scalable and maintainable. - Architecting Microservices
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Design and implement microservices architecture to enhance system modularity and scalability. - CI/CD Pipeline Implementation
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Develop and maintain Continuous Integration and Continuous Deployment (CI/CD) pipelines to streamline the software development lifecycle. - Collaboration
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Work closely with cross‑functional teams, including product management, design, and QA, to deliver high‑quality software solutions that align with business goals. - Mentorship
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Provide guidance and mentorship to junior developers, fostering a culture of continuous learning and improvement within the team. - Continuous Improvement
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Contribute to the continuous improvement of development practices, ensuring the adoption of best practices and modern technologies. - AI Systems Development
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Design and implement multi‑agent AI systems using frameworks like Lang Chain, Auto Gen, and CrewAI, and develop AI‑powered decision engines and autonomous task execution systems. - Event‑Driven Architectures
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Implement event‑driven architectures using message queues such as Azure Service Bus and Rabbit
MQ to enhance system responsiveness and scalability. - Data Preparation
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Utilize Azure Data Factory to create ETL/ELT pipelines for AI data preparation, ensuring data is ready for analysis and model training. - Infrastructure Management
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Leverage Azure Dev Ops for CI/CD pipelines and Infrastructure as Code (ARM/Bicep) to manage cloud resources efficiently. - Workflow Orchestration
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Use Azure Logic Apps for complex workflow orchestration and B2B integrations, ensuring seamless data flow across systems. - Monitoring and Observability
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Implement monitoring and observability tools to ensure system reliability and performance.
- C# /.NET
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Proficiency in C# and .NET framework for backend development, including experience with .NET Core for building scalable applications. - Python
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Strong knowledge of Python for backend services, data processing, and AI‑related tasks. - Microservices Architecture
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Experience in designing and implementing microservices architecture, focusing on modularity and scalability. - Azure Cloud Services
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In‑depth knowledge of Azure Cloud services for deployment, orchestration, and management of cloud resources. - Dev Ops Practices
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Familiarity with Dev Ops practices, including CI/CD pipelines, Infrastructure as Code (IaC), and automated testing. - Multi‑Agent AI Systems
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Experience in designing and implementing multi‑agent AI systems using frameworks like Lang Chain, Auto Gen, and CrewAI. - RAG Pipelines
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Ability to build Retrieval‑Augmented Generation (RAG) pipelines with vector databases such as Pinecone and Weaviate. - LLM Fine‑Tuning
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Experience with fine‑tuning large language models (LLMs) and optimizing prompt engineering for improved performance. - AI‑Powered Decision Engines
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Knowledge in developing AI‑powered decision engines and autonomous task execution systems. - Event‑Driven Architectures
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Experience with event‑driven architectures using message queues like Azure Service Bus and Rabbit
MQ. - Azure Data Factory
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Proficiency in using Azure Data Factory for creating ETL/ELT…
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