Senior AI Engineer

Open Innovation AI; Abu Dhabi; On-site; AED 420,000 - 660,000; Full time

Job summary

Open Innovation AI in Abu Dhabi is hiring a Senior AI Engineer to build the applied AI that powers our agentic platform. You will translate cutting-edge LLM research into reliable, production-ready features and systems.

You will prototype, test, deploy, and monitor models, explore new techniques, and collaborate with product and engineering teams to turn user needs into concrete specs while helping junior engineers grow.

Qualifications

• Degree in CS or engineering or equivalent experience.
• Strong Python or TypeScript.
• Experience shipping applied AI/ML to real users.
• Hands-on with LLMs and orchestration toolsets (RAG, prompts).
• Exposure to MLOps/LLMOps: deploying and monitoring models in production.
• Solid software architecture understanding.
• Proficient with Git and collaborating across teams.
• Ability to explain decisions and progress under deadlines.

Responsibilities

• Write clean, reliable code for agentic and applied-AI features.
• Bring LLM capabilities into production: agents, flows, RAG, tool use, multiagent setups.
• Prototype and evaluate new models and techniques.
• Build evals, benchmarks, and observability for model progress.
• Maintain production AI workloads with automation and scaling.
• Collaborate with product and other teams to turn needs into specs.
• Debug, test, and tune core product performance.
• Review code and mentor junior engineers.

Skills

Python/TS

LLMs & Agents

MLOps

Software Architecture

Git

Deadline-driven

Education

CS or Engineering degree

Tools

Orchestration frameworks

RAG pipelines

Prompt engineering tools

Job description

Open Innovation AI is a global technology company that specializes in developing advanced solutions for managing AI workloads. Its flagship product, the Open Innovation Cluster Manager (OICM), orchestrates complex AI tasks efficiently across diverse infrastructures. The platform is hardware-agnostic, optimized for various GPUs and accelerators hardware, and facilitates seamless integration and scalability for enterprise AI applications. Open Innovation AI focuses on optimizing and simplifying AI workload management and making AI technologies accessible to organizations of all sizes. With its innovative solutions, companies can reduce operational costs, accelerate time to value, and maximize their return on investment, ensuring that their AI strategies contribute directly to enhanced business outcomes

Role Overview:

We're hiring an Senior AI Engineer to build the applied AI that our agentic platform runs on. The job is to take what's working in LLMs and agent systems right now and turn it into features people can depend on. Some of it is straight engineering. Some of it is keeping up with a field that moves every week reading the new work, trying it, and shipping the parts that hold up.

Role Responsibilities:

• Write clean, reliable code for the agentic and applied-AI features at the core of the product
• Get LLM capabilities into production: agents, orchestration flows, RAG, tool use, multiagent setups
• Try new models, techniques, and frameworks. Prototype them, see if they hold up, bring the good ones in
• Build the evals, benchmarks, and observability we need to actually know whether an agent is getting better or worse
• Keep AI workloads running in production automation, scaling, the unglamorous parts
• Work with product and other teams to turn what users need into specs you can build against
• Debug, test, and tune the core product when it's slow or wrong
• Review code and help junior engineers level up
• Keep an eye on what's new and flag what's worth the team's attention

Required experience & Qualification

• A degree in CS or engineering, or the equivalent experience we care more about what you've built.
• Strong Python or TypeScript. Either is fine.
• You've built applied AI or ML and shipped it to real users, not just in notebooks.
• Hands-on with LLMs and the current toolset: orchestration frameworks, agentic patterns, RAG, prompt engineering, fine-tuning, evals a solid subset of these.
• Some exposure to MLOps/LLMOps: deploying, scaling, and monitoring models in production.
• Real grounding in software design. You should be able to reason about architecture, not just wire up API calls.
• Comfortable with Git.
• You can make progress on a deadline and explain your thinking to the people around you

Nice to have:

• A strongly typed language like Go, Java, or C++
• Open-source contributions, papers, or applied research
• The habit of reading AI research and actually turning it into product changes