AI Engineer (Full Stack) - Must be UAE Based

LogiX; Abu Dhabi; Hybrid; AED 180,000 - 260,000; Full time

Job summary

LogiX, Abu Dhabi-based data and AI solutions provider, seeks a senior software/AI engineer to own production AI applications. You will design end-to-end agentic workflows using Python, FastAPI, React, PostgreSQL, and Azure OpenAI, with SAP and M365 integrations and human-in-the-loop controls.

You will drive model selection, evaluation, and deployment, ensuring observability, reliability, and collaboration with clients to translate data strategies into scalable AI products.

Qualifications

• 7+ years software/AI engineering experience.
• 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 LangGraph, Semantic Kernel, AutoGen 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.

Responsibilities

• Build end-to-end agentic workflows with multi-step orchestration and human-in-the-loop controls.
• Develop and operate production AI/LLM systems with observability and debugging.
• Integrate AI applications with SAP, Microsoft 365 / Microsoft Graph and enterprise APIs.

Skills

Python

FastAPI

React

PostgreSQL

Azure OpenAI

LangGraph

Semantic Kernel

AutoGen

LLM evaluation

RAG & retrieval

API design

Agentic AI development

Tool calling

SAP

Microsoft 365 / Graph

Tools

SAP

Microsoft Graph

LangGraph

Semantic Kernel

AutoGen

Job description

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.

Role Description - Mandatory Expertise

• 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.

Qualifications

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 LangGraph, Semantic Kernel, AutoGen 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.