Technical Product Manager
Skills
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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