Join our team as a Custom Software Engineer, focusing on Full Stack development with a blend of AI-first innovation. This role is crucial for designing, developing, and deploying enterprise-grade solutions utilizing Generative and Agentic AI frameworks.

We are seeking forward-thinking professionals who can drive innovation, enhance efficiency, and contribute to business transformation through AI-powered technologies. The position emphasizes hands-on development and practical solution design, making a significant impact on our clients' digital strategies.

Lead the design and delivery of AI-driven solutions, applying GenAI and Agentic AI to tackle complex business challenges. Automate processes and integrate intelligent insights into enterprise workflows for measurable results.

Key duties include hands-on coding in Java Spring Boot and Python, contributing to front-end development with React or Angular, and designing scalable, cloud-native application architectures. Develop and maintain integrations using APIs and microservices, deploy applications across multi-cloud environments (AWS, Azure, Google Cloud), and implement practical AI features.

Collaborate with DevOps teams on containerized solutions and CI/CD pipelines, ensure application performance and security, and work closely with cross-functional teams. Continuously learn and stay updated on full-stack development trends, cloud technologies, and AI advancements.

We are looking for Application Architects or Senior Developers with 5-12 years of full-stack development experience, including at least 2 years in a lead or junior architect role. A strong foundation in Java Spring Boot and Python for backend, coupled with hands-on experience in front-end frameworks like React or Angular, is essential.

Demonstrated experience with multi-cloud environments (AWS, Azure, Google Cloud), integration patterns (REST APIs, message queues), and microservices architecture is required. Familiarity with Docker, Kubernetes, IaC tools like Terraform, and cloud-native services is also necessary.

Basic exposure to AI/ML integration, working knowledge of DevOps practices, and understanding of secure coding practices are expected. Strong problem-solving skills, clear communication, and a willingness to learn are vital for success in this collaborative role.