Role Summary The AI Architect is responsible for designing end-to-end AI/ML and GenAI solution architectures that translate business requirements into scalable, production-grade systems. This role bridges technical strategy and delivery, working closely with AI/ML Engineers, GenAI Engineers, and client stakeholders to ensure solutions are robust, secure, and aligned with enterprise architecture standards.

Key Responsibilities
• Design and own end-to-end architecture for AI/ML and GenAI solutions, including data pipelines, model serving, orchestration, and integration layers
• Evaluate and select appropriate frameworks, cloud services, and toolchains (e.g., Azure AI, AWS, GCP, LLM providers, vector databases)
• Define architecture patterns for RAG systems, agentic workflows, MLOps/LLMOps pipelines, and model governance
• Partner with client stakeholders and internal delivery teams to translate business problems into technical solution designs
• Establish best practices for scalability, security, cost optimization, and responsible AI/model risk management
• Conduct architecture reviews and provide technical guidance to engineering teams during implementation
• Create solution blueprints, reference architectures,



and technical documentation for proposals and delivery
• Stay current with emerging AI/ML technologies and assess their applicability to client and internal use cases
• Support pre-sales activities including solutioning, effort estimation, and technical proposal development Required Qualifications
• Bachelor's/Master's degree in Computer Science, Engineering, or related field
• 8+ years in software/data architecture, with 3+ years focused on AI/ML or GenAI solution design
• Strong hands-on background in ML system design, cloud architecture (Azure/AWS/GCP), and MLOps practices
• Experience architecting LLM-based applications (RAG, agents, fine-tuning, prompt orchestration)
• Familiarity with data engineering, APIs, microservices, and enterprise integration patterns
• Strong communication skills for client-facing architecture discussions Preferred
• Relevant cloud/AI certifications (e.g., Azure AI Engineer/Solutions Architect)
• Experience in a consulting or skilled services environment
• Exposure to model governance, responsible AI frameworks, and cost/performance optimization at scale

📌 AI Architect (Chennai)
🏢 Agilisium Consulting
📍 Chennai