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Technical Product Manager

Socium - Teams Done DifferentlyAbu Dhabi, UAE1 weeks agoMid-Senior
Mid-Seniorcontract

Skills

GitMachine LearningAIProduct ManagementCloud
Apply For This Job
Via LinkedIn·

About This Role

General Description

Join a fast-growing, AI-driven organization in Abu Dhabi building next-generation AI platforms and intelligent systems at scale.

The organization focuses on delivering

enterprise-grade AI ecosystems

, combining AI/ML, cloud infrastructure, and data platforms to power large-scale digital transformation initiatives across enterprise and government environments.

Their work centers on building

production-ready AI platforms

, including LLM-based systems, intelligent automation, and scalable AI infrastructure.

We are looking for experienced

MLOps / AI Platform Engineers (Senior / Lead level)

to design, build, and scale production-grade AI and machine learning platforms.

This role focuses on delivering end-to-end AI systems, including LLM-based applications, ML workflows, and backend services that power enterprise and large-scale AI use cases.

This role is ideal for engineers with strong experience in

AI/ML systems, backend development, and cloud infrastructure

, who can bridge the gap between model development and real-world production deployment.

This is a

6-month contract role (extendable)

with

full onsite presence in Abu Dhabi

.

Key Responsibilities

  • Design and build scalable AI platforms supporting ML workflows and LLM-based applications
  • Develop and deploy AI/ML models into production environments using MLOps best practices
  • Build and maintain backend services and APIs (Python, FastAPI) for AI-powered systems
  • Implement and optimize RAG pipelines and LLM-based solutions using tools like LangChain and LlamaIndex
  • Manage containerized deployments using Docker and Kubernetes in cloud environments (AWS/Linux)
  • Establish and maintain CI/CD pipelines for ML and AI workloads (Jenkins, Terraform, DVC, MLflow)
  • Implement model serving and orchestration using tools such as KServe
  • Work with vector databases and data systems (FAISS, PostgreSQL, Redis) to support AI applications
  • Monitor system performance, reliability, and observability using Prometheus and Grafana
  • Collaborate with cross-functional teams including AI/ML engineers, backend developers, and platform teams to deliver high-quality AI systems.

Required Skills & Experience

  • Strong experience as an MLOps Engineer, AI Platform Engineer, or Backend Engineer with AI/ML exposure
  • Proven experience deploying ML models or AI systems into production (not just experimentation)
  • Hands-on experience with LLMs, RAG pipelines, or GenAI-based applications
  • Strong programming experience in Python with backend frameworks such as FastAPI
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Experience working in cloud environments (AWS or similar) and Linux systems
  • Familiarity with MLOps tools such as MLflow, KServe, DVC, Jenkins, or Terraform
  • Experience working with data systems, vector stores, and caching layers (PostgreSQL, Redis, FAISS)
  • Understanding of monitoring, logging, and observability tools (Prometheus, Grafana)
  • Experience working in scalable, distributed systems and microservices architectures.

Duration

6 months (extendable)

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