Join us as a Senior Full Stack Engineer and drive innovation by developing custom software solutions. You will be instrumental in designing, coding, and enhancing complex system components, leveraging modern frameworks and agile methodologies.

This role emphasizes an AI-first mindset, focusing on enterprise-grade solutions using Generative and Agentic AI to foster efficiency and business transformation. You'll work with cutting-edge technologies to create scalable, high-performing applications tailored to specific business needs.

Lead the design and delivery of AI-driven solutions, applying Generative and Agentic AI to solve intricate business challenges and automate workflows.

Take ownership of hands-on coding, rigorous testing, and deployment of application-heavy solutions. Develop clean, efficient code in Java Spring Boot or Python, and contribute to front-end development using React or Angular.

Collaborate with senior architects to design scalable, cloud-native application architectures, prioritizing performance, maintainability, and seamless integration across multi-cloud environments.

Develop and maintain robust integrations using APIs, microservices, and event-driven patterns, ensuring efficient data flow.

Implement and optimize applications across AWS, Azure, and Google Cloud, focusing on cost-effectiveness and peak performance.

Integrate practical AI features, such as automation and analytics, utilizing cloud-based AI services or frameworks.

Partner with DevOps teams for containerized solutions and CI/CD pipelines, employing Infrastructure as Code tools.

Ensure applications meet stringent performance and security standards through comprehensive code reviews and testing.

Foster strong team collaboration, translating requirements into technical implementations and providing hands-on mentorship.

A minimum of 5 years of extensive full-stack development experience is required, with at least 2 years in a lead developer or junior architect capacity for application-heavy systems.

Demonstrated success in building and deploying solutions within multi-cloud environments (AWS, Azure, Google Cloud) is essential.

Proficiency in Java Spring Boot and Python for backend development is a must, alongside hands-on experience with front-end frameworks like React or Angular.

Basic exposure to AI/ML integration, including cloud AI services or simple ML frameworks, is expected.

Practical experience with integration patterns like REST APIs and message queues, along with microservices architecture, is crucial.

Familiarity with infrastructure tools such as Docker, Kubernetes, and Infrastructure as Code (e.g., Terraform) is required.

Experience with cloud-native services and a solid understanding of DevOps practices, including CI/CD pipelines and monitoring tools, are necessary.

Knowledge of secure coding practices and fundamental enterprise security standards (e.g., IAM, encryption) is important.

Strong debugging and problem-solving skills, a hands-on approach, clear communication, and an eagerness to learn are key soft skills for this role.