Solution Architect

Requirements

• Support the architecture and design of AI solutions across multiple projects, ensuring technical feasibility and alignment with client goals
• Contribute to the development of shared architectural patterns, reusable components, and design practices to support both experimental and production-ready AI initiatives
• Evaluate client needs, system constraints, and platform environments to recommend scalable and secure AI designs across cloud, on-prem, or hybrid setups
• Drive architectural decisions related to data pipelines, model orchestration, API development, observability, and integration with enterprise systems
• Apply knowledge of traditional machine learning and generative AI technologies (e.g., LLMs, embeddings, RAG, AI agents) to support diverse solution needs
• Understand and work with orchestration layers and protocols (e.g., tool use, function calling, and emerging standards like MCP) that support multi-step reasoning and agentic workflows
• Serve as a technical resource to project teams by reviewing technical designs, contributing to code and system architecture, and mentoring junior engineers
• Collaborate with delivery leads, and client stakeholders to refine solution designs as project requirements evolve
• Participate in technology evaluation and internal discussions to help shape best practices and strengthen architectural consistency across teams

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