Description

Job Description:
Roles & 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.
Professional & 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.
We are seeking a dynamic Mid-Level Application Architects / Senior Developers with a strong focus on hands-on development and practical solution design. The ideal candidate will have robust experience in .NET Core, MVC, and Python, with working knowledge of front-end technologies like React or Angular, and a foundational understanding of AI integration. This role emphasizes active coding, solution implementation, and collaboration across application development, infrastructure, and integration in multi-cloud environments (AWS, Azure, Google Cloud) to deliver scalable, secure enterprise applications.
Key Responsibilities:
Hands-On Coding: Actively develop, test, and deploy application-heavy solutions, write clean, efficient code in any of the programming languages like .NET Core (C#, ASP.NET), and Python for backend systems, and contributing 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 BiCep.
Performance & 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

Key Skills

Education

Any Graduate