Principal AI Engineer

Principal AI Engineer

Smart Connected Solutions (SCS) — Dubai, UAE

About Us

Smart Connected Solutions builds AI-powered automation for enterprise systems. We turn complex, real-world data and fragmented platforms into reliable, auditable automation that organizations trust in production.

About the Role

We're looking for a Principal AI Engineer who owns AI systems end to end — from the architecture on the whiteboard to the code in production. You'll work across a wide range of enterprise problems, combining backend engineering depth with applied LLM expertise. This is a senior builder's role: you set the technical direction, and you ship it, taking systems from first prototype through deployment, operation, and iteration.

Salary range: AED 15,000 - AED 18,000 /month

What You'll Be Working On

•  AI systems, end to end:  Architect and implement production AI applications and agentic workflows, owning each one from concept to running system.

•  Enterprise integrations:  Connect AI systems to enterprise platforms, APIs, and external services through integration layers you design and build.

•  Data and document pipelines:  Turn messy, real-world unstructured data into production-grade extraction and processing pipelines.

•  MLOps and DevOps:  Stand up and run the deployment, CI/CD, and monitoring infrastructure behind your systems — you ship and operate what you build.

•  Technical direction:  Define the architecture patterns, evaluation strategy, and guardrails for how we build AI, and prove them out in code.

•  Production quality:  Drive observability, evaluation, latency, and cost across AI workloads.

What We're Looking For

• Strong backend engineering background with production Python; you build systems meant to run, not demos.

• A track record of carrying AI systems solo across the full lifecycle — design, implementation, deployment, and operation.

• Experience building  agentic / LLM-based systems , with a clear point of view on system design and reliability.

• Experience integrating AI with  enterprise systems and APIs .

• Practical  RAG and document intelligence  experience, including the data-quality realities of production.

• Solid  MLOps and DevOps  foundation: CI/CD, containerization, deployment, monitoring, and infrastructure. Experience with Git workflows and repository management. 

• Sound judgment on  production LLM concerns : evaluation, latency, cost, and scaling.

• Ability to operate as a technical leader — owning ambiguous problems end to end and setting direction for others

Nice to Have

• Experience delivering  multi-tenant SaaS or enterprise-grade solutions .

• Computer vision or multilingual NLP experience.

• Familiarity with modern cloud and deployment stacks.

• Computer vision experience (e.g., layout/document models, YOLO-family).

• Comfort across the deployment stack (Render, containerized deploys, CI/CD).

• Mobile app development experience