Fullstack Developer - .NET

Seeking a forward-thinking professional with an AI-first mindset to design, develop, and deploy enterprise-grade solutions using generative and agentic AI frameworks that drive innovation, efficiency, and business transformation.

Responsibilities:

• Lead AI-driven solution design and delivery by applying GenAI and Agentic AI to address complex business challenges, automate processes, and integrate intelligent insights into enterprise workflows for measurable impact.
• Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
• Hands-On Coding: Actively develop, test, and deploy application-heavy solutions, writing clean, efficient code in any of the programming languages, such as. NET Core (C#, ASP. NET) and Python for backend systems, and contribute to front-end development using React or Angular.
• Solution Design: Partner with senior architects to design scalable, cloud-native application architectures, focusing on performance, maintainability, and integration in multi-cloud environments.
• Integration Development: Build and maintain integrations using APIs, microservices, and event-driven patterns (e. g., REST, GraphQL, Kafka, or message queues).
• Multi-Cloud Implementation: Develop and deploy applications across AWS, Azure, and Google Cloud, ensuring portability and optimization for cost and performance.
• AI Integration: Implement practical AI features (e. g., automation, basic analytics) using cloud-based AI services or frameworks like TensorFlow or PyTorch.
• Infrastructure Support: Collaborate with DevOps teams to implement containerized solutions (Docker, Kubernetes) and CI/CD pipelines, with hands-on use of IaC tools like Terraform or BiCE.
• Performance and Security Optimization: Ensure applications meet performance and security standards through code reviews, testing, and adherence to best practices.
• Team Collaboration: Work closely with developers, product managers, and infrastructure teams to translate requirements into technical implementations, providing hands-on support and mentorship.
• Continuous Learning: Stay updated on full-stack development trends, cloud technologies, and AI advancements to contribute to innovative solutions.

Requirements:

• Bachelor's degree in computer science, engineering, or a related field.
• Certifications like Azure Developer Associate, Azure AI Fundamentals, or similar are a plus.
• Experience: 5 to 10 years of hands-on experience in full-stack development, with at least 2 years in a lead developer or junior architect role focusing on application-heavy systems.
• Demonstrated experience building and deploying solutions in multi-cloud environments (AWS, Azure, Google Cloud).
• Strong proficiency in NET and Python for backend development.
• Hands-on experience with front-end frameworks like React, Angular, or similar.
• Basic exposure to AI/ML integration, such as using cloud AI services (e. g., Azure OpenAI, Azure Foundry, AWS SageMaker) or simple ML frameworks.
• Practical experience with integration patterns (e. g., REST APIs, message queues) and microservices architecture.
• Familiarity with infrastructure tools like Docker, Kubernetes, and IaC (e. g., Terraform, Bicep).
• Experience with cloud-native services (e. g., Azure Functions, Logic Apps, Service Bus, etc. ).
• Working knowledge of DevOps practices, including CI/CD pipelines and monitoring tools.
• Understanding of secure coding practices and basic enterprise security standards (e. g., IAM, encryption).

Soft Skills:

• Strong debugging and problem-solving skills with a hands-on mindset.
• Clear communication to collaborate with technical and non-technical stakeholders.
• Ability to juggle hands-on coding with architectural design contributions.
• Eagerness to learn and adapt to new tools, frameworks, and cloud technologies.

Professional and Technical Skills:

• Strong grasp of generative and agentic AI, prompt engineering, and AI evaluation frameworks.
• Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization.