Artificial Intelligence Engineer

Tanqeeb; Dubai; On-site; AED 240,000 - 420,000; Full time

Job summary

Tanqeeb is hiring an AI Engineer in Dubai to design, build, and deploy AI agents and LLM-powered features integrated with CRM and messaging tools. You will architect reusable components, enforce strict output schemas, and drive quality through evals and testing.

Strong Python, LLM API experience, and API integration skills are essential for this client-facing infrastructure role. The role emphasizes hands-on backend work with FastAPI/Flask, REST, OAuth, webhooks, and cloud deployment.

Qualifications

• 2+ years of production software experience with hands-on LLM work.
• Strong Python experience with backend frameworks (FastAPI or Flask).
• Hands-on experience with LLM APIs and prompt engineering.
• Experience with API integration patterns (OAuth 2.0, webhooks, REST).
• Familiarity with SQL and vector/embedding stores.
• Version control with Git and basic CI/CD exposure.
• Good communication to explain trade-offs to non-technical stakeholders.

Responsibilities

• Design, build, and deploy AI agents and LLM-powered features.
• Integrate AI systems with third-party platforms via REST APIs, OAuth, and webhooks.
• Build reusable components and typed tool contracts with enforced output schemas.
• Set up and run evals to catch quality drops before production.
• Collaborate with Product/Engineering to convert requirements into agent behavior and document architecture.

Skills

Python

LLM APIs

Prompt engineering

Function calling

Context management

REST APIs

OAuth 2.0

Webhooks

SQL

Git

CI/CD

Communication

Tools

Docker

Kubernetes

AWS

GCP

Azure

FastAPI

Flask

Anthropic API

OpenAI API

Nango

Git

Job description

AI Engineer

Location: Dubai Experience: 2 to 5 years Work Type: Full-time, Work From Office (WFO)

What You'll DoDesign, build, and deploy AI agents and LLM-powered features — prompt/harness design, tool orchestration, structured outputs. Integrate AI systems with third-party platforms — CRMs, messaging channels, support tools — via REST APIs, OAuth, and webhooks. Build and maintain reusable components (prompt libraries, guardrails, validation logic) instead of one-off scripts per use case. Write typed tool contracts and enforce output schemas (Pydantic or equivalent) to keep agent behavior predictable and testable. Set up and run evals — trajectory evals, regression tests — to catch quality drops before they reach production. Work with Product/Engineering to turn requirements into working agent behavior, and document architecture clearly enough for handoff.

What We're Looking For Experience: 2–5 years building production software, with meaningful hands-on LLM work Strong Python — comfortable with Fast API or Flask for backend services. Practical experience with LLM APIs (Anthropic, Open AI, or open-source models) — prompt engineering, function calling/tool use, context management. Working knowledge of API integration patterns — OAuth 2.0, webhooks, REST, sync vs. async/event-driven design. Familiarity with SQL and at least one vector/embedding store. Version control (Git) and basic CI/CD exposure. Clean, process-oriented coding habits — this is client-facing infra, not a hackathon. Good communication - able to explain technical trade-offs to non-technical stakeholders.

Bonus Points For Experience with agentic coding tools (Claude Code, Cursor) in your own workflow. Exposure to voice agents, multi-channel conversational AI, or real-time streaming systems. Experience with self-hosted auth/OAuth tooling (Nango or similar) over managed platforms. Docker/Kubernetes and basic cloud deployment (AWS/GCP/Azure) experience. Startup background — comfortable owning ambiguous problems without a fully specced ticket.