Job Summary
AI Fullstack Engineer
Role Summary
The AI Fullstack Engineer designs, builds, and delivers end-to-end AI-powered applications by combining modern frontend frameworks with backend services and Generative AI capabilities. This role focuses on integrating Large Language Models (LLMs) into real user experiences such as copilots, AI assistants, and intelligent workflows, while ensuring scalability, performance, and usability.
Key Responsibilities
• Build end-to-end AI-powered applications using modern frontend and backend technologies.
• Integrate Large Language Models (LLMs) into user-facing workflows and experiences.
• Develop AI-enabled features such as chat interfaces, copilots, summarization, and intelligent search.
• Design and implement responsive UIs using React, Angular, or similar frameworks.
• Build backend services and APIs to orchestrate LLM calls, RAG pipelines, and AI workflows.
• Implement prompt engineering, embeddings, and Retrieval-Augmented Generation (RAG).
• Ensure application performance, scalability, security, and reliability.
• Collaborate with UX designers, AI engineers, and product teams.
Required Skills & Experience
• Strong experience with frontend frameworks such as React or Angular.
• Backend development experience using Python, Node.js, or Java.
• Hands-on experience integrating LLMs (OpenAI, Azure OpenAI, Gemini, Claude, or open-source models).
• Experience with prompt engineering, embeddings, and RAG pipelines.
• Familiarity with REST/GraphQL APIs, Docker, cloud platforms, and CI/CD pipelines.
• Basic exposure to MLOps or LLMOps concepts is a plus.
Experience Level
• 8+ years of fullstack or application engineering experience.
• 2+ years of hands-on experience delivering AI or GenAI-enabled applications.
Success Measures
• AI features seamlessly integrated into production user workflows.
• High adoption and usability of AI-powered applications.
• Stable, scalable, and secure fullstack AI solutions running in production.
Key Responsibilities
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.