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AI Engineer

Location: Tehran
Technology
Posted: Sep 12, 2026

Iranian Company in Automotive Industry
Annual Package: 0.8 – 1.2 billion Tomans
On-site | Part-time



Responsibilities

·        Develop and implement AI solutions using LLMs, intelligent agents, and multi-agent architectures.

·        Design and develop RAG-based systems using embeddings, vector databases, and reliable knowledge retrieval.

·        Design scalable AI architectures and integrate LLM-based solutions with enterprise applications and APIs.

·        Develop intelligent agents capable of interacting with business systems, APIs, documents, and structured data.

·        Implement and optimize AI solutions using frameworks such as LangChain, Semantic Kernel, GraphRAG, and MCP.

·        Develop prompt engineering strategies and optimize model performance, response quality, latency, and token costs.

·        Design AI Governance, security, access control, and risk management practices for AI systems.

·        Implement mechanisms for hallucination detection, source citation, validation, and reliable AI responses.

·        Evaluate AI models, architectures, and emerging technologies and translate them into practical business solutions.

·        Collaborate with Software Engineering, Data, Product, and Business teams to deploy and continuously improve AI-powered applications.


Requirements

·        3–5+ years of experience in Software Development and AI Engineering.

·        Strong proficiency in Python or C# and modern software development practices.

·        Advanced knowledge of LLMs, AI APIs, and intelligent agent architectures.

·        Strong experience implementing RAG pipelines, embeddings, and Vector Databases.

·        Hands-on experience with LangChain, Semantic Kernel, or similar AI frameworks.

·        Experience with Multi-Agent Systems, GraphRAG, MCP, and enterprise AI solutions.

·        Strong knowledge of prompt engineering and LLM performance optimization.

·        Familiarity with PyTorch and modern machine learning frameworks.

·        Strong understanding of AI security, governance, hallucination control, and responsible AI practices.

·        Experience integrating AI solutions with APIs, .NET applications, enterprise systems, and business workflows.

 

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