Role:Experience Level: 10+ Years
location: QATAR
Note :communication (Arabic & English). Gulf nationals only.
Machine Learning & Generative AI Engineer (Mid-Level)
ML | DL | Python | LangChain/LangGraph | Azure AI Foundry | RAG | Vector Stores | Semantic Kernel
Role Summary
Build and deploy enterprise-grade Generative AI solutions with strong grounding and
measurable quality. You will implement RAG pipelines, agentic workflows
(LangChain/LangGraph/ Semantic Kernel), and evaluation/monitoring on Azure AI Foundry
and Azure services, or GCP.
Key Responsibilities
- Implement end-to-end RAG: ingestion, chunking, embeddings, retrieval, reranking,
and citation/grounding.
- Develop agentic workflows using Semantic Kernel, LangChain and LangGraph
(tools, routing, memory) with guardrails and safe tool use.
- Integrate vector stores/search (Azure AI Search vector, Pinecone, Weaviate, Milvus,
pgvector, or equivalent) and maintain reliable data pipelines.
- Build Python services/APIs (FastAPI preferred) with streaming, auth (Entra ID/OIDC
as applicable), and production-ready error handling.
- Own quality and operations: golden datasets, automated regression evaluation,
tracing/observability, and latency/cost optimization (caching, batching).
Required Qualifications
- 3-6 years software engineering experience; 1-3 years delivering ML/GenAI features
to production.
- Strong Python, API development, unit/integration testing, and Git-based workflows
(Azure DevOps or GitHub).
- Hands-on experience with RAG patterns, embeddings, retrieval strategies, prompt
design, and LLMs evaluation basics.
- Experience with Azure AI Foundry / Azure OpenAI and deploying on Azure
(Container Apps, Functions, App Service,
- or AKS).
- Comfortable working with data and documents; strong communication and
documentation skills.
Great Advantage
- LLMOps: prompt/version governance, tracing (LangSmith/OpenTelemetry), and
evaluation frameworks.
- Hybrid search and reranking, structured outputs (JSON schema), and prompt-
injection/tool-safety mitigations.
- Performance testing and cost optimization experience for LLM-based systems.
- Bilingual communication (Arabic & English).
Typical Tech Stack
- Python (FastAPI), LangChain, LangGraph, Azure AI Foundry, Azure OpenAI, Azure AI
Search (vector), Semantic Kernel, PyTroch, Keras, Tensorflow.
- Pinecone/Weaviate /pgvector / Azure AI Search, Docker, Azure DevOps, Key Vault,
Application Insights.
Skills: vector,python,rag,kernel,ml,azure
