Full Stack AI Engineers

Key Responsibilities

• Backend & API Engineering: Build and scale robust backend services and microservices using Node.js/TypeScript and Python.
• AI Orchestration: Design and implement agentic workflows, multi-agent coordination, and tool-calling structures using frameworks like LangChain, CrewAI, or AutoGen.
• Semantic Knowledge Management: Implement Retrieval-Augmented Generation (RAG) pipelines and historical pattern matching utilizing PostgreSQL (including vector extensions).
• Frontend Implementation: Develop clean, high-performance interfaces using React or Next.js to visually render AI reasoning paths, interactive timelines, and system workflows.
• System Optimization & Deployment: Fine-tune prompts and orchestration logic to reduce latency and token usage; containerize and deploy services using Docker across cloud environments.

Required Skills & Qualifications

• Experience: 4+ years of professional full-stack software development experience.
• Languages: Proficient in TypeScript/JavaScript (Node.js) and Python.
• Databases: Hands-on experience with PostgreSQL, alongside exposure to high-scale data layers like ClickHouse or time-series databases.
• AI & LLM Knowledge: Practical experience integrating LLMs (OpenAI, Anthropic, or open-source models) and executing agentic patterns (memory, tool-use, planning).
• Frontend Tech: Strong experience with modern frontend frameworks (React.js or Next.js), state management tools, and clean UI design layouts.
• DevOps/Infrastructure: Familiarity with Docker containerization, major cloud platforms (AWS, GCP, or Azure), and setting up automated CI/CD pipelines.