AI Engineer Urgently Needed

Client of Hirelebanese

As an AI Engineer, you will architect and build the "intelligence layer" of our platform. You will move beyond simple RAG (Retrieval-Augmented Generation) to design Agentic Systems, intelligent workflows capable of reasoning, planning, and executing complex tasks autonomously.


Key Responsibilities:

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- Agentic Architecture: Design and implement multi-agent orchestration patterns using frameworks like LangGraph.

- LLM Strategy: Select, fine-tune, and optimize Large Language Models (LLMs) from providers like OpenAI and Anthropic, or open-source alternatives (Llama 3, Mistral).

- Advanced RAG & Memory: Build sophisticated retrieval pipelines using vector databases (Pinecone, Weaviate) and implement long-term memory for agents to learn from user interactions.

- Tool Integration: Implement Function Calling and protocols like the Model Context Protocol (MCP) to allow agents to interact with our platform s APIs and databases.

- Guardrails & Safety: Establish evaluation frameworks to measure hallucination rates, bias, and latency. Build "break-glass" mechanisms for human-in-the-loop (HITL) intervention.



Technical Skills & Requirements:

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- Machine Learning & LLMs

Deep Learning: Mastery of Transformer architectures, attention mechanisms, and tokenization.

- Model Optimization: Experience with prompt engineering, few-shot learning, and fine-tuning techniques.

- Evaluation: Knowledge of RAGAS, DeepEval, or custom benchmark suites to validate non-deterministic outputs.

- Agentic AI & Orchestration

Frameworks: Proficiency in LangChain/LangGraph, LlamaIndex, or Semantic Kernel.

- Understanding of task decomposition, self-reflection loops, and multi-agent communication protocols.

- Expert-level Python.

- Data Infrastructure: Experience with Vector DBs and traditional databases.

- DevOps/AIOps: Familiarity with containerization and cloud AI stacks.


Experience Qualifications:

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- Total Experience: 7+ years in Software Engineering or Data Science.

- AI Leadership: 2+ years leading AI/ML initiatives, specifically involving Generative AI or LLMs in a production environment.

- Portfolio: Proven track record of moving a GenAI project from demo to a scaled production app with real users.