Join our team as a Custom Software Engineer and play a vital role in developing innovative, scalable software solutions. This full-time position focuses on creating custom applications using modern frameworks and agile methodologies, designed to meet specific business needs and drive efficiency. You will be instrumental in enhancing components across various systems and applications, ensuring high performance and seamless integration.

This role offers the opportunity to work with cutting-edge technologies, including Generative and Agentic AI, to build enterprise-grade solutions that foster innovation and business transformation. If you're a forward-thinking professional with a passion for AI and a strong development background, this is an exciting opportunity to make a significant impact.

Develop and enhance custom software components, ensuring scalability and high performance. Design and implement solutions using modern frameworks and agile practices. Utilize Generative and Agentic AI to address complex business challenges and automate processes. Integrate intelligent insights into enterprise workflows for measurable business impact. Collaborate with senior architects on designing scalable, cloud-native application architectures. Build and maintain integrations using APIs, microservices, and event-driven patterns. Deploy and optimize applications across multi-cloud environments (AWS, Azure, Google Cloud). Implement practical AI features and integrate cloud-based AI services. Collaborate with DevOps teams on containerization and CI/CD pipelines. Ensure applications meet stringent performance and security standards. Mentor junior team members and provide hands-on technical support.

A Bachelor's degree in Computer Science, Engineering, or a related field is required. Minimum of 2 years of experience in full-stack development is essential, with 5-12 years preferred. Proven experience in .NET Core, MVC, and Python for backend development. Hands-on experience with front-end frameworks like React or Angular. Familiarity with multi-cloud environments (AWS, Azure, Google Cloud). Basic exposure to AI/ML integration and cloud AI services. Practical experience with integration patterns (e.g., REST APIs, message queues) and microservices. Familiarity with containerization (Docker, Kubernetes) and IaC tools like Terraform. Understanding of DevOps practices, CI/CD pipelines, and secure coding standards. Strong problem-solving abilities and clear communication skills are essential.