AI Engineer; Full Stack; UAE

Company Description LogiX helps organizations unlock the full value of their data by transforming business operations through advanced data strategies and artificial intelligence solutions. The company partners with clients across industries to design, build, and deploy AI-powered products that improve efficiency, decision-making, and customer experiences. LogiX emphasizes practical, scalable implementations that integrate seamlessly with existing systems. Team members collaborate closely with clients and internal stakeholders to deliver measurable impact and long-term innovation.

• Build agentic workflows end-to-end:
  Python/FastAPI, React, PostgreSQL, Azure OpenAI (UAE North) - multi-step orchestration, tool calling, human-in-the-loop gates, on SAP, M365 and external data.

• Strong ML/AI foundations:
  Model selection and evaluation, classical ML where it outperforms LLMs, retrieval quality, and production monitoring.

• Production-grade engineering:
  You’ve built and operated agent systems in production. AI-assisted development is expected, but you fully own, understand, debug, and can explain your code.

7+ years software/AI engineering experience, with recent hands-on delivery of production AI/LLM applications.

Python & FastAPI — strong production development experience, including APIs and backend services.

Agentic AI development — hands-on experience building multi-step agent workflows, including tool/function calling, orchestration, state management and human-in-the-loop controls.

LLM frameworks — strong hands-on experience with Lang Graph, Semantic Kernel, Auto Gen or equivalent.

Azure OpenAI / Azure AI — experience developing and deploying enterprise AI solutions on Microsoft Azure.

RAG & retrieval engineering — embeddings, vector/hybrid search, reranking, grounding and retrieval evaluation.

Strong ML/AI fundamentals — model selection, evaluation, classical ML, LLM evaluation and understanding when not to use an LLM.

Production AI engineering — demonstrated experience deploying and operating agent/LLM systems in production, including observability, evaluation, monitoring, debugging, reliability and failure handling.

SQL & PostgreSQL — strong ability to work directly with structured enterprise data and design/query relational data models.

Enterprise integrations — hands-on experience connecting AI applications to enterprise systems and APIs, including authentication, permissions and secure data access.

Experience integrating AI applications with complex enterprise systems and APIs.

Hands-on integration experience with SAP and/or Microsoft 365 / Microsoft Graph.

Full ownership of code — able to independently design, build, test, debug and explain production code, including code produced using AI-assisted development tools.