Pre-Sales AI Solution Engineer

Omni Ops is a Riyadh-based technology solutions provider, serving organizations across Saudi Arabia and beyond. With offices in Jordan, Egypt, and Morocco, we specialize in empowering businesses to migrate and scale their AI technology infrastructure confidently, achieving a high level of maturity in their digital landscapes. Our comprehensive services and products guarantee seamless cloud migration, scalability, and management, ensuring optimal performance and consistent reliability for our valued partners.

We are looking for a Pre‑Sales AI Solution Engineer with a solid understanding of Generative AI, Agentic AI architectures, and AI infrastructure. The role combines hands‑on AI solution development, technical pre‑sales, and customer engagement to support enterprise AI opportunities.

• Engage with customers to understand requirements and propose suitable AI solutions.
• Design high-level architectures for Generative AI, RAG, AI agents, and enterprise AI platforms.
• Develop and demonstrate AI prototypes, demos, and Proofs of Concept (PoCs) for customer use cases.
• Prepare technical proposals, architecture diagrams, RFP responses, and solution presentations.
• Support AI infrastructure discussions, including GPU accelerators, deployment architecture, and high-level capacity sizing.
• Collaborate with sales, engineering, and delivery teams throughout the pre-sales cycle.

• Minimum 5 years of experience in technical pre‑sales, solution engineering, software engineering, or related roles.
• Good understanding of LLMs, RAG, Agentic AI, and AI orchestration concepts.
• Hands‑on experience building AI applications, demos, prototypes, or PoCs.
• Familiarity with AI frameworks such as Lang Chain, Lang Graph, or similar.
• Good understanding of Kubernetes and Docker, including containerized application deployment and orchestration.
• Understanding of AI infrastructure, GPU accelerators (NVIDIA or equivalent), and inference workloads.
• Working knowledge of Python, APIs, and system integration.
• Familiarity with cloud, on‑premises, or hybrid deployment architectures.
• Strong technical presentation, documentation, and customer communication skills.
• Professional proficiency in English.

• Exposure to vLLM, Slang or other LLM inference‑serving frameworks.
• Familiarity with GPU configuration, multi‑GPU deployments, and infrastructure sizing.
• Experience with NVIDIA AI software or GPU computing environments.
• Previous experience in enterprise AI solution consulting or pre‑sales.

• Customer‑focused with strong problem‑solving skills.
• Able to translate business requirements into practical AI architectures.
• Comfortable communicating with both technical and business stakeholders.
• Proactive, collaborative, and eager to learn emerging AI technologies.