Join our team as a Custom Software Engineer, where you'll craft innovative solutions using modern frameworks and agile methodologies. This role is perfect for a forward-thinking professional with an AI-first mindset, eager to design, develop, and deploy enterprise-grade solutions.

Leverage Generative and Agentic AI frameworks to drive innovation, enhance efficiency, and transform business processes. You will be instrumental in applying AI to address complex business challenges, automate workflows, and integrate intelligent insights for measurable impact.

As a Custom Software Engineer, you will lead the design and delivery of AI-driven solutions, integrating GenAI and Agentic AI to solve intricate business problems. Responsibilities include automating processes and embedding intelligent insights into enterprise workflows.

You will be actively involved in hands-on coding, developing, testing, and deploying robust application-heavy solutions. This includes writing efficient code in Java Spring Boot and Python, and contributing to front-end development with React or Angular.

Collaborate with senior architects on scalable, cloud-native application architectures and build integrations using various patterns and technologies. You will also deploy applications across multi-cloud environments, implement practical AI features, and support DevOps initiatives with containerization and CI/CD.

Ensure applications meet high performance and security standards through rigorous testing and adherence to best practices. Teamwork is key, so you'll work closely with various teams to translate requirements into technical solutions and mentor colleagues.

Continuously stay updated on the latest full-stack development trends, cloud technologies, and AI advancements to foster innovation.

This role requires 2-5 years of hands-on full-stack development experience, including at least 2 years in a lead developer or junior architect capacity focusing on application-heavy systems.

Demonstrated expertise in building and deploying solutions within multi-cloud environments such as AWS, Azure, and Google Cloud is essential. Strong proficiency in Java Spring Boot and Python for backend development, along with hands-on experience in front-end frameworks like React or Angular, is crucial.

Basic exposure to AI/ML integration, utilizing cloud AI services or simple ML frameworks, is expected. Practical experience with integration patterns, microservices architecture, and familiarity with infrastructure tools like Docker, Kubernetes, and IaC (e.g., Terraform) are also required.

A solid understanding of DevOps practices, including CI/CD pipelines and monitoring tools, is necessary. Knowledge of secure coding practices and basic enterprise security standards is also important.

Soft skills include strong debugging and problem-solving abilities, clear communication for stakeholder collaboration, the capacity to balance coding with architectural contributions, and a proactive eagerness to learn new technologies.