Pre-Sales AI Solution Engineer

About OmniOps

Role overview

Key responsibilities

• 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 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.

Required qualifications

• Minimum five 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 proofs of concept.
• Familiarity with AI frameworks such as LangChain, LangGraph, 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.

Preferred skills

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

Role attributes