Artificial Intelligence Expert

Job Description

In addition to its main activities in the field of supplying equipment and implementing industrial and infrastructure projects, Faraz Energy Pod Engineering Company is committed to the future of digital security. In this regard, we are proud to be the official business partner of QuCypher.
QuCypher is an advanced cybersecurity consultancy specializing in Post-Quantum Readiness. The company makes large global organizations resistant to emerging threats posed by quantum computers (which are capable of breaking classical cryptographic algorithms).

Job description:

This position is defined to develop secure and scalable AI-based systems in our AI Services phase. The focus is on implementing multi-agent workflows under strict sandboxing rules and using RAG for accurate model grounding.

Responsibilities:

Building multi-agent orchestration flows under robust sandboxing.
Implement safe Tool-Calling Patterns.
Integration of RAG (Retrieval Augmented Generation) with Vector Search Using Abstract Schemas.
Development of model routing logic and platform management (Context Management Logic).
Implementation of hallucination detection mechanisms (Hallucination Detection) or Critic/Self-Check patterns.

Required skills and experience:

Core Proficiency: Complete and deep mastery of Python programming language, especially in data science and machine learning ecosystem (expert use of NumPy, Pandas and ML and DL related libraries for data preprocessing and management).
LLM Frameworks: Hands-on experience with LangChain, CrewAI or LlamaIndex.
Model Deployment: Experience in deploying and tuning VLLM/Ollama.
Vector DB: Proficiency in Weaviate or similar vector databases.
Substrate Engineering: Deep knowledge about embeddings behavior and substrate engineering.
Expertise: Strong Discipline in Prompt Engineering.
Experience in building operational workflows at the production level (Production-quality).

It is considered an advantage if:

Experience with Multi-step Reasoning or Agent Chaining.
Have experience working with enterprise-safe AI design.
Have knowledge about phenomena like Embedding Drift and Context Collapse.