Join our team as a Custom Software Engineer, where you'll be instrumental in designing, coding, and enhancing system components. This role focuses on developing tailored software solutions using modern frameworks and agile methodologies to deliver scalable, high-performance applications that meet specific business requirements.

We are seeking a forward-thinking professional with an AI-first mindset. You will design, develop, and deploy enterprise-grade solutions leveraging Generative and Agentic AI frameworks to drive innovation, efficiency, and business transformation.

As a Full Stack Engineering Analyst, you will contribute to building robust and intelligent enterprise solutions. This position emphasizes hands-on development and practical solution design within multi-cloud environments.

Lead the design and delivery of AI-driven solutions, applying GenAI and Agentic AI to tackle complex business challenges and integrate intelligent insights. Develop, test, and deploy application-heavy solutions, writing clean, efficient code in Java Spring boot or Python for backend systems, and contributing to front-end development with React or Angular.

Collaborate with senior architects to design scalable, cloud-native application architectures. Build and maintain integrations using APIs, microservices, and event-driven patterns. Implement practical AI features and automate processes.

Develop and deploy applications across AWS, Azure, and Google Cloud, ensuring portability and optimization. Work closely with DevOps teams on containerized solutions and CI/CD pipelines. Stay updated on full-stack development trends, cloud technologies, and AI advancements.

A minimum of 2 years of hands-on experience in full-stack development is required, with a strong focus on application-heavy systems and Java Full Stack Development.

We require proficiency in Java Spring boot and Python for backend development, alongside hands-on experience with front-end frameworks such as React or Angular. Basic exposure to AI/ML integration, including the use of cloud AI services or simple ML frameworks, is necessary.

Demonstrated experience building and deploying solutions in multi-cloud environments (AWS, Azure, Google Cloud) is essential. Familiarity with integration patterns, microservices architecture, containerization tools (Docker, Kubernetes), and IaC tools (Terraform) is expected. A Bachelor's degree in Computer Science, Engineering, or a related field is required.