About the Role
As an AI Full-Stack Engineer, you will join our product and engineering team to build production-grade AI applications from concept to deployment.
You will work across the full technology stack, including frontend development, backend services, LLM integrations, AI agent frameworks, and workflow automation. This role offers the opportunity to contribute directly to products used by real customers while working at the forefront of applied AI.
Responsibilities
Build AI-Powered Products
- Develop and deploy AI applications powered by Large Language Models (LLMs)
- Design and implement capabilities such as:
- Retrieval-Augmented Generation (RAG)
- Function Calling
- AI Agent Workflows
- Multi-Agent Orchestration
- Integrate external APIs, data platforms, and business systems into AI-powered solutions
Full-Stack Development
- Build scalable backend services and APIs
- Develop intuitive frontend interfaces for AI products
- Design and maintain data pipelines and application architecture
- Collaborate with product and engineering teams to deliver end-to-end solutions
Optimize AI Performance
- Design and improve prompt engineering workflows
- Implement embedding, retrieval, and knowledge management systems
- Improve AI accuracy, reliability, and production readiness
- Monitor and evaluate model performance in real-world environments
Research & Innovation
- Stay current with the latest AI models, tools, frameworks, and infrastructure
- Evaluate emerging technologies and identify opportunities for product adoption
- Contribute ideas and prototypes that accelerate product innovation
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or related disciplines
- Strong interest in Artificial Intelligence and emerging technologies
- Experience building software projects, AI applications, automation workflows, or personal technical projects
- Understanding of full-stack development fundamentals
- Familiarity with modern AI tools, LLMs, and developer workflows
- Strong problem-solving ability and willingness to learn quickly in a fast-paced environment
Preferred Qualifications
- Experience with AI frameworks, agent architectures, or RAG systems
- Familiarity with cloud platforms and modern software deployment practices
- Exposure to Web3, blockchain technologies, digital assets, or decentralized applications
- Open-source contributions, technical portfolios, or GitHub projects demonstrating engineering capability
- Evidence of building products or solutions that created measurable value for users
What We Offer
Real Ownership
Work on production-grade AI products used by real customers—not internal demos or experimental side projects.
Accelerated Learning
Gain hands-on exposure to cutting-edge AI technologies, modern engineering practices, and emerging industry trends.
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