AI Engineer

Company OverviewOpen 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 AI Engineer to build the applied AI that our agentic platform runs on. The job is to take what's actually 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, multi-agent 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 & QualificationA degree in CS or engineering, or the equivalent experience we care more about what you've builtStrong 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 callsComfortable with Git.You can make progress on a deadline and explain your thinking to the people around youNice 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.