AI Solutions Architect

About the Position

The AI Solutions Architect acts as the strategic link between complex business requirements and practical AI implementations. This role requires a blend of high-level consulting, technical architecture, and product thinking. The successful candidate will guide clients through the technical discovery phase, map business needs to existing or custom AI capabilities, and design scalable, end-to-end solution roadmaps.

About the Project

This project involves leading high-impact AI discovery and implementation initiatives. The goal is to assist clients in navigating the rapidly evolving Generative AI landscape by designing bespoke architectures—including RAG systems, AI agents, and automation workflows—that solve specific business challenges and drive operational efficiency.

Responsibilities

• Lead technical discovery sessions and workshops to identify business goals, pain points, and technical constraints.
• Translate client requirements into detailed AI solution designs, implementation frameworks, and integration strategies.
• Recommend optimal AI technologies, LLMs, platforms, and tools based on specific use cases.
• Evaluate whether requirements should be addressed via existing platforms or through custom-developed AI solutions.
• Produce comprehensive technical documentation, solution proposals, and accurate effort estimates for delivery teams.
• Partner with engineering, product, and delivery teams to ensure the successful transition from design to implementation.
• Assist in pre-sales discussions and technical presentations to demonstrate the value of proposed AI architectures.
• Maintain expert-level knowledge of emerging trends in GenAI, RAG, vector databases, and automation.

Requirements

• Deep understanding of the AI/ML ecosystem, including modern Generative AI capabilities, LLMs, and AI agent frameworks.
• Proven experience designing RAG systems, vector database integrations, and complex automation workflows.
• Demonstrated ability to translate abstract business problems into scalable, technical AI architectures.
• Exceptional ability to articulate complex technical concepts to non-technical stakeholders and executive leadership.
• Practical experience with major cloud platforms (AWS, Azure, or GCP).
• Strong capability in conducting build-vs-buy assessments and defining technical roadmaps.

Nice to Have

• Background in pre-sales engineering or AI product strategy.
• Expertise in enterprise-grade software integrations and complex workflow automation.
• Experience leading formal AI discovery or design-thinking workshops.
• Previous professional experience in software engineering or general system architecture.