AI Engineer

Role & responsibilities

• Design, build, test, and deploy AI agents on multiple low-code / no-code platforms

like Microsoft Copilot Studio, N8N, Make, Helix Studio, Oracle AI Studio, and other

emerging agentic platforms.

• Craft high-quality system prompts, user prompts, and instruction sets that guide

agent behaviour including chain-of-thought reasoning, tool-calling directives,

guardrails, and fallback logic.

• Architect agentic workflows encompassing multi-step reasoning, tool use, memory

management, context grounding, and human-in-the-loop escalation patterns.

• Integrate AI agents with enterprise systems (CRM, ERP, ITSM, HRMS, core

banking, etc.) via REST/SOAP APIs, MCP servers, A2A protocol, Power Automate

connectors, webhooks, and custom plugins.

• Build and manage multi-agent orchestration patterns including delegation, sub-

agent routing, conditional branching, and cross-platform agent interoperability using

A2A and similar protocols.

• Develop custom scripts (Python, JavaScript/TypeScript) for scenarios where low-

code capabilities are insufficient — e.g., data transformation, API middleware,

custom MCP servers, or evaluation harnesses.

• Design and implement Retrieval-Augmented Generation (RAG) pipelines for

knowledge-grounded agents, including document ingestion, chunking strategies,

embedding, and vector store integration.

• Create structured evaluation frameworks for agents — including golden test sets,

Exact Match, LLM-as-a-Judge scoring, prompt regression testing, and automated

quality gates.

• Collaborate with business stakeholders to identify automation opportunities, define

agent scope, and translate requirements into actionable agent specifications.

• Maintain comprehensive documentation of agent architectures, prompt libraries,

integration patterns, and deployment runbooks.

• Stay current with the rapidly evolving agentic AI landscape — new platforms,

protocols (MCP, A2A, ACP), frameworks (LangChain, LangGraph, AutoGen,

Semantic Kernel, CrewAI), and best practices.

• Support governance and compliance requirements by implementing appropriate

guardrails, content filters, audit trails, and role-based access controls within agent

deployments.

Preferred candidate profile

• Microsoft certifications: AI-102 (Azure AI Engineer), PL-200 (Power Platform

Functional Consultant), or the upcoming AB-620 (Copilot Studio AI Agent Builder).

• UiPath certifications: UiPath Certified Automation Developer or Agentic Automation

Developer Associate.

• Experience with agentic frameworks such as LangChain, LangGraph, AutoGen,

Semantic Kernel, or CrewAI.

• Familiarity with evaluation and observability tools: LangSmith, Weights & Biases,

Application Insights, Datadog.

• Experience building custom MCP servers or implementing A2A agent discovery and

task delegation.

• Knowledge of responsible AI principles, content filtering, PII handling, and AI

governance frameworks.

• Exposure to RPA (Robotic Process Automation) tools and their integration with

agentic AI workflows.

• Multi-language LLM prompting experience (English + Arabic is a plus for a Dubai-

based role).