Full Stack Agentic AI Engineer

The Role Your role: As a Full-Stack Agentic AI Engineer at Kyndryl, you will translate architectural blueprints into robust, production-ready code to drive next-generation customer solutions. In this hands-on, highly technical position, you will build and seamlessly integrate autonomous AI capabilities directly into enterprise-level software systems. What you will do: Develop and implement end-to-end AI-driven applications, integrating generative AI models Build and maintain scalable front-end interfaces using modern web frameworks (React, Angular, Vue.js) Design and develop robust back-end services using Node.js, Python, or other back-end technologies Integrate large language models (LLMs) and multimodal AI models into applications Optimize application performance, ensuring efficiency in AI inference and API response times Develop and maintain RESTful and GraphQL APIs for AI model interaction Deploy AI applications on cloud platforms (AWS, GCP, Azure) using containerization and serverless technologies Ensure security, scalability, and compliance of AI-driven applications Stay up to date with the latest advancements in Generative/Agentic AI, web development, and cloud technologies Who You Are You re good at what you do and possess the required experience to prove it. However, equally as important you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused someone who prioritizes customer success in their work. And finally, you re open and borderless naturally inclusive in how you work with others. Required Skills & Qualifications Bachelor s degree in computer science, Software Engineering, or a related field (or equivalent experience). 6+ years of experience in full-stack development, with a track record of building scalable, production-ready systems. Strong proficiency in JavaScript/TypeScript, Python, and modern front-end frameworks (React, Vue, or Angular). Experience with agentic frameworks such as LangChain, AutoGen or CrewAI. Hands-on experience with integrating AI models via APIs (OpenAI, Hugging Face, etc.). Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) techniques. Experience with cloud platforms (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD pipelines. Strong understanding of database technologies (SQL, NoSQL, Firebase, MongoDB, PostgreSQL). Ability to design scalable and maintainable architectures for AI-driven applications. Capable of working closely with cross-functional teams to deliver cohesive, end-to-end functionality. Knowledge of message queues (e.g., RabbitMQ, Kafka) and caching systems (e.g., Redis). Preferred Skills & Qualifications Experience with Temporal Workflows, Langfuse, LLM gateways such as LiteLLM Prior experience in prompt engineering Experience in building AI-powered chatbots, content generators, or recommendation systems. Familiarity with LLM fine-tuning, prompt engineering, and AI model optimization. Knowledge of serverless computing, edge AI, and streaming architectures. Background in handling large-scale data or real-time systems. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.