Join our team as a Custom Software Engineer, focusing on building innovative solutions with a strong emphasis on Generative and Agentic AI. This role is perfect for a forward-thinking professional passionate about AI-first development, aiming to design, develop, and deploy enterprise-grade solutions. We leverage modern frameworks and agile practices to deliver scalable, high-performing applications tailored to unique business requirements.

This position emphasizes hands-on coding and practical solution design, with opportunities to work across application development, infrastructure, and integration in multi-cloud environments. Your contributions will drive innovation and efficiency, making a tangible impact on business transformation.

As a Custom Software Engineer, you will lead AI-driven solution design, applying GenAI and Agentic AI to solve complex business challenges. Your responsibilities include automating processes and integrating intelligent insights into enterprise workflows for measurable impact.

Key duties involve hands-on coding, developing and testing application-heavy solutions, and writing clean, efficient code in Java Spring boot or Python. You'll also contribute to front-end development using React or Angular. Partner with senior architects on scalable, cloud-native application design, focusing on performance and integration. Build and maintain integrations via APIs, microservices, and event-driven patterns. Deploy applications across AWS, Azure, and Google Cloud, ensuring portability and optimization. Implement practical AI features and collaborate with DevOps for containerized solutions and CI/CD pipelines.

We are seeking a dynamic Application Architect or Senior Developer with a robust background in full-stack development, ideally with 2-5 years of experience. A strong command of Java Spring boot and Python for backend systems is essential, complemented by working knowledge of front-end technologies like React or Angular.

Essential skills include Generative and Agentic AI, prompt engineering, and AI evaluation frameworks. Experience in multi-cloud environments (AWS, Azure, Google Cloud) and with integration patterns like REST APIs and microservices is crucial. Familiarity with Docker, Kubernetes, and infrastructure-as-code tools such as Terraform is expected. Basic exposure to AI/ML integration and DevOps practices is also required. Strong debugging, problem-solving skills, clear communication, and an eagerness to learn are vital.