Senior Agentic AI Engineer — On-Prem Production Lead

DISCOVERED; Dubai; On-site; AED 240,000 - 360,000; Full time

Job summary

DISCOVERED in Dubai is seeking a Senior Agentic AI Engineer to own the end-to-end lifecycle of production AI solutions. You will design and deploy agent workflows using self-hosted LLMs, integrate with enterprise systems, and build backend services for production reliability.

You'll lead architecture decisions, optimize performance, and collaborate with Product and Engineering to deliver scalable AI products in both cloud and on-prem environments, using Docker, Kubernetes, CI/CD, and MLOps

Qualifications

• 5+ years' experience across AI or Machine Learning Engineering.
• Strong hands-on experience building and deploying production-grade Generative AI and Agentic AI systems.

Responsibilities

• Design and build AI agent applications using self-hosted LLMs and modern agentic frameworks, focusing on privacy, security and control.
• Own the wider AI lifecycle including deployment, monitoring, versioning, and optimization.
• Collaborate with Product, Engineering and business stakeholders to deliver commercial AI products that balance performance, cost and speed to market.
• Provide technical leadership and hands-on contribution across the stack, from architecture to production operations.

Skills

AI/ML engineering

Production AI systems

Self-hosted LLMs

Python

LangChain / frameworks

RAG & prompt engineering

Docker & Kubernetes

CI/CD & MLOps

Secure system design

Cloud & on-prem deployment

Education

Master's degree in CS/Data Science or related field

Tools

LLaMA

Mistral

GPT/Claude

LangChain

Semantic Kernel

CrewAI

MCP-based architectures

Docker

Kubernetes

CI/CD

Job description

DISCOVERED in Dubai is seeking a Senior Agentic AI Engineer to own the end-to-end lifecycle of production AI solutions. You will design and deploy agent workflows using self-hosted LLMs, integrate with enterprise systems, and build backend services for production reliability.

You'll lead architecture decisions, optimize performance, and collaborate with Product and Engineering to deliver scalable AI products in both cloud and on-prem environments, using Docker, Kubernetes, CI/CD, and MLOps