Key Responsibilities Act as the technical lead in the sales cycle, partnering with Account Executives to drive enterprise opportunities from qualification to close. Have a perspective on how AI can drive value in Enterprises and understand the power of language models and agents to impact business value across verticals and business functions. Understand customer pain points in driving and implementing AI solutions. Deliver compelling technical presentations, demos showcasing Gen AI, Agentic AI, RAG, and LLM-based solutions. Build and deliver custom demos and POCs to validate business value and technical feasibility. Conduct discovery sessions with key business and technical stakeholders to uncover needs, pain points, and desired outcomes. Translate business requirements into AI solution architectures that leverage Company's capabilities, collaborating with product and engineering teams. Respond to RFPs/RFIs with detailed technical responses and solution designs. Advise clients on AI adoption strategies, integration with multi-modal data platforms, and industry best practices. Contribute to a culture of technical excellence, customer obsession, and innovation. Build and maintain deep domain expertise in AI trends, competitor offerings, and the evolving landscape of agentic applications and enterprise AI adoption. Skills and Qualifications 6+ years of experience in pre-sales, solution engineering, or technical consulting – preferably within enterprise Saa S, AI, or automation platforms. Hands-on understanding of AI concepts: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, Agentic AI architectures, AI security and governance, and ethical AI Experience designing or selling AI platforms, data orchestration, or enterprise automation solutions. Expertise in major Cloud Platforms: Demonstrated understanding of cloud computing principles and architecture, particularly as they relate to deploying and scaling enterprise AI/Saa S solutions (e.g., AWS, Azure, or GCP). This includes familiarity with core services like compute, storage, networking, and serverless functions. Solid Understanding of API Integration and Security: Practical experience with designing, integrating, and securing API connections between AI platforms and underlying business applications (e.g., CRM, ERP, data warehouses). Knowledge of protocols (e.g., REST, Graph QL) and authentication mechanisms (e.g., OAuth 2.0, API keys) is essential. Data and Network Architecture Acumen: Ability to discuss and propose solutions regarding data governance, network segmentation, and enterprise security requirements when deploying cloud-native or hybrid AI solutions. Strong ability to explain technical concepts to both technical and non-technical stakeholders. Proven track record supporting enterprise sales cycles and closing large deals. Excellent communication, presentation, and stakeholder management skills with the ability to engage with all levels within large enterprises, from C-suite to technician. Strong problem-solving and storytelling skills—able to connect AI capabilities to strategic business outcomes. Ability to travel as needed for client engagements.