AI Full-Stack Engineer

What will you do

• Design, build, and maintain production-grade AI-powered applications and services.
• Develop end-to-end full-stack solutions, including backend services, APIs, and modern React-based frontends.
• Build scalable, secure, and highly available distributed systems.
• Develop AI agents, copilots, autonomous workflows, and intelligent automation.
• Build and deploy RAG (Retrieval-Augmented Generation) solutions and integrate LLMs into production.
• Design AI orchestration workflows using frameworks such as LangChain, LangGraph, or similar.
• Implement AI evaluation, tracing, and observability pipelines using Langfuse or equivalent tools.
• Develop MCP (Model Context Protocol) integrations and AI tooling ecosystems.
• Build and maintain cloud infrastructure, CI/CD pipelines, and Infrastructure-as-Code.
• Drive engineering productivity through AI-assisted development and automation.
• Collaborate closely with Product, Design, and Engineering teams to deliver customer value.
• Research and evaluate emerging AI technologies and introduce innovative solutions.
• Own features end-to-end—from architecture and development to deployment, monitoring, and continuous improvement.

What will you have

• 5+ years of experience building scalable, production-grade full-stack applications.
• Strong hands-on experience with TypeScript, Node.js, Python, React, and modern full-stack development.
• Experience building AI-powered applications using LLMs (OpenAI, Anthropic, Gemini, etc.).
• Hands-on experience with AI Agents, RAG, vector databases, prompt engineering, context engineering, and MCP.
• Experience with AI frameworks such as LangChain, LangGraph, Langfuse, LlamaIndex, or similar.
• Strong understanding of distributed systems, microservices, APIs, and cloud-native architectures.
• Experience with AWS, Docker, Kubernetes, CI/CD, and DevOps best practices.
• Ability to quickly learn and adopt emerging AI technologies and AI-assisted development tools.
• Strong ownership mindset with the ability to independently deliver solutions from concept to production.
• Experience building internal AI platforms or AI developer tools (advantage).
• Familiarity with AI coding assistants such as Cursor, Claude Code, Windsurf, or GitHub Copilot (advantage).
• Experience with multi-agent systems and autonomous workflows (advantage).
• Background in SaaS or cybersecurity environments (advantage).
• Experience leading technical initiatives or mentoring engineers (advantage).
• Knowledge of AI security, model safety, and governance best practices (advantage).
• Excellent communication skills, a collaborative mindset, and the ability to thrive in a fast-paced startup environment.
• Passion for AI, curiosity, and a strong focus on innovation, execution, and business impact.