What You’ll Do

• Design, develop, and deliver AI-powered features across Easygenerator’s products.
• Work with modern LLM frameworks and toolchains (LangChain, LangGraph, LangFuse, etc.) to build RAG systems, AI Agents, and dynamic authoring workflows.
• Work in a highly capable cross-functional team environment (Engineering, Product, and Design) to integrate AI seamlessly into our well architected and distributed product.
• Apply solid AI engineering principles — from planning and testing to deployment, evaluation, and continuous improvement.
• Optimize and fine-tune open-source or hosted LLMs to balance performance, accuracy, and cost.
• Contribute to LLMOps and AI observability, improving reliability, evaluation, and monitoring pipelines.
• Stay on top of emerging AI tools and frameworks, helping shape Easygenerator’s AI vision and roadmap.

• 2+ years of experience building and deploying production-grade AI applications.
• 4+ years of web application engineering experience
• Solid understanding of machine learning and deep learning fundamentals.
• Practical knowledge of LLMs, their components (tokenization, attention, embeddings, vector search), and common limitations.
• Hands-on experience with RAG pipelines, Agents, and Vector Stores.
• Familiarity with LLMOps practices — monitoring, evaluation, and feedback loops.
• Strong understanding of software engineering principles and SDLC.
• Comfortable working beyond notebooks — building APIs, services, and integrations.
• Strong understanding of high-level programming language like Python.
• Good understanding of version control, CI/CD, testing frameworks, and data handling/ETL.
• Working knowledge of Docker and containerized environments.
• Familiarity with AWS or other cloud providers. (Plus)
• Basic experience with a backend framework (e.g., FastAPI, Express.js or similar). (Big Plus)

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