AI Integration Engineer

We’re looking for a hands-on AI Integration Engineer who’s passionate about automation and eager to build real-world AI systems.

You’ll work deep in the stack — designing data pipelines, integrating LLMs via APIs, and building production-ready workflows with tools like n8n, Zapier, Make, and Airflow.

If you love solving complex problems, experimenting with cutting-edge AI tools, and turning ideas into scalable automation — this role is for you.

REQUIREMENTS

• 3+ years of experience as a Software, Systems, or Integration Engineer
• Proven expertise with n8n and similar tools (Zapier, Make, Airflow, etc.)
• Strong programming skills in Python, JavaScript, or similar languages
• Experience integrating AI models and platforms (OpenAI, Anthropic Claude, Google Gemini, Hugging Face, etc.)
• Experience with vector databases (Pinecone, Weaviate, ChromaDB) for RAG pipelines
• Familiarity with prompt engineering and optimization techniques
• Experience working with APIs, data pipelines, and system integrations
• Understanding of real-time data streaming (Kafka, Redis)
• Experience with data transformation, cleaning, and preprocessing pipelines
• Fast learner, comfortable with emerging AI technologies and frameworks
• Knowledge of modern AI integration patterns, such as:
• Function calling and tool usage
• Agent-to-Agent communication (AtoA)
• Model Context Protocol (MCP)
• LangChain / LangGraph or similar orchestration frameworks
• Proven experience implementing AI-driven solutions in production
• Strong analytical, troubleshooting, and problem-solving skills
• Upper-Intermediate English or higher

Would Be a Plus

• Hands-on experience with cloud environments (AWS, GCP, Azure)
• Proficiency in Git and CI/CD workflows
• Experience with AI agent frameworks (AutoGPT, CrewAI, LangChain Agents, etc.)
• Background in MLOps or AIOps practices
• Contributions to open-source AI or automation projects

RESPONSIBILITIES

• Design, build, and maintain AI-powered workflows using n8n and other automation tools
• Integrate AI models, APIs, and third-party services into production systems
• Implement advanced AI features such as function calling, agent orchestration, and multi-model workflows
• Ensure system stability through robust error handling and fallback mechanisms
• Optimize workflow performance, latency, and cost
• Set up metrics and monitoring for workflow accuracy and performance
• Collaborate with product and engineering teams to deliver scalable AI-driven solutions
• Document integration pipelines, best practices, and conduct internal knowledge-sharing sessions
• Continuously explore and adopt new AI tools and technologies to improve automation efficiency

WE OFFER

• 20 vacation days (workdays)
• 7 sick days
• Personalized career growth
• Internal English classes
• Education reimbursement
• Corporate events and team buildings
• Equipment provided