AI Engineer

Role Purpose

Design, build, test, and operate enterprise AI and Generative AI capabilities supporting Mashreq’s AI CoE, Agentic AI Ecosystem, Enterprise AI Platform, and Trade Virtual Assistant. The role delivers secure, reusable, and observable AI services aligned with Mashreq’s AI Strategy, engineering standards, and digital transformation priorities.

Key Responsibilities

Strategic Responsibilities

• Contribute to reusable AI engineering patterns, platform accelerators, and technical standards.


• Assess suitable LLM, RAG, agent, MCP, tool-calling, and function-calling approaches against business and non-functional needs.

Delivery Responsibilities

• Develop Python-based AI services, prompt workflows, RAG pipelines, embeddings, retrieval, AI agents, and multi-agent components.


• Configure and integrate Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.


• Implement APIs, tool integrations, function calling, data connectors, automated tests, evaluation datasets, CI/CD, and MLOps pipelines.


• Monitor quality, latency, reliability, safety, and cost; investigate defects and support controlled production releases.


• Produce maintainable code, technical documentation, deployment instructions, and operational runbooks.

Governance Responsibilities

• Apply Responsible AI, security, privacy, compliance, access-control, content-safety, and data-handling requirements.


• Maintain traceability for prompts, models, retrieval sources, evaluations, changes, and releases.


• Support architecture, security, risk, and governance reviews and remediate identified control gaps.

Stakeholder Management Responsibilities

• Work with the Senior AI Engineer, AI Architect, product owners, business analysts, data teams, platform teams, and vendors.


• Explain engineering progress, dependencies, risks, and technical choices clearly to delivery stakeholders.

Required Experience

• 5–7 years in software, data, ML, or AI engineering with hands-on enterprise delivery.


• Practical experience with GenAI, LLMs, prompt engineering, RAG, AI agents, multi-agent systems, MCP, tool calling, and function calling.


• Hands-on Azure AI experience including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.


• Experience with Python, APIs, containers, CI/CD, MLOps, observability, testing, and enterprise integration.


• Banking or financial-services exposure preferred, including retail, corporate, trade finance, digital banking, risk, or compliance.

Required Skills

Skill Group

Required Skills

Technical Skills

Python; LLM application development; Prompt engineering; RAG; AI agents; Multi-agent systems; MCP; Tool calling; Function calling; Automated evaluation

Platform Skills

Azure OpenAI; Azure AI Foundry; Azure AI Search; Azure Functions; AKS; Azure API Management; Microsoft Fabric; Git and CI/CD

Integration Skills

REST APIs; Data connectors; Event integration; Authentication and authorization; Enterprise application integration

Governance & Security Skills

Responsible AI; AI governance; Security and compliance; MLOps; Observability; Model and prompt monitoring; Enterprise standards

Leadership / Business Skills

Problem solving; Agile delivery; Documentation; Collaboration; Clear stakeholder communication

Preferred Tools and Certifications

Certification

Relevance

Requirement

Microsoft Certified: Azure AI Engineer Associate

Build and deploy AI solutions on Microsoft Azure.

Preferred

Microsoft Certified: Azure Fundamentals

Demonstrate foundational Azure cloud knowledge.

Preferred

Generative AI Certification

Apply LLM, prompt, RAG, and responsible GenAI practices.

Preferred

Python Certification

Demonstrate applied Python programming capability.

Preferred

Education

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related discipline is mandatory. A Master’s degree is preferred.