Gen AI Engineer

Job description

Job Title: Full-Stack Engineer (AI/GenAI Focus) Experience: 8+ Years Role Overview We are seeking an experienced Full-Stack Engineer with a strong focus on AI-enabled applications and GenAI technologies. The ideal candidate will design, develop, and deploy scalable full-stack solutions, integrating modern frontend frameworks with robust backend systems while leveraging AI/ML and LLM capabilities to drive intelligent automation and user experiences. Key Responsibilities • Design and develop end-to-end full-stack applications, including frontend, backend, and data integrations • Build AI-enabled applications, automations, and agentic workflows • Develop intuitive user interfaces using modern frontend technologies (e.g., React, Angular, or similar frameworks) • Implement backend services using Python, Java, or JavaScript/TypeScript • Design and integrate APIs (RESTful and event-driven architectures) • Develop and maintain data pipelines and service integrations • Evaluate and implement LLM-based solutions where appropriate, ensuring optimal UX beyond traditional chatbot paradigms • Collaborate with Product Managers, Business Analysts, UX designers, and Architects to define and refine technical solutions • Deploy and manage applications in cloud-native environments, with a strong preference for Microsoft Azure • Ensure performance, scalability, security, and maintainability of applications Required Skills Qualifications • 8+ years of experience in full-stack development • 3 to 5 years of strong expertise in frontend frameworks such as React, Angular, or equivalent • 3 to 5 years of proficiency in backend technologies including Python, Java, or Node.js/TypeScript • 3 to 5 years of experience with API design, development, and integration (REST, microservices, event-driven systems) • 3 to 5 years of hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face • 1 to 3 years of experience working with GenAI and LLM platforms (e.g., OpenAI APIs, Azure OpenAI, LangChain) • Familiarity with cloud-native development, preferably on Microsoft Azure • Strong understanding of software architecture, design patterns, and scalable systems Preferred Qualifications • Experience with low-code/no-code platforms, particularly OutSystems • Exposure to building intelligent automation and workflow orchestration solutions • Understanding of prompt engineering and LLM application design patterns • Experience with DevOps practices, CI/CD pipelines, and containerization (Docker/Kubernetes)