AI Solution Architect

Role Overview: AI Studio in India is seeking an AI Solution Architect to drive end-to-end ownership of high-impact AI use-cases from problem framing to production deployment. This role operates at the intersection of business-technology outcomes and applied AI, orchestrating rapid prototyping, scalable architecture design, and delivery of parallel MVPs and products across multiple use-cases within compressed timelines. You will engage directly with business stakeholders to surface outcome metrics, drive rapid prototyping cycles, lead concurrent delivery of multiple AI use-cases, and ensure compliance with enterprise security, privacy, and governance standards. Additionally, you will own the lifecycle from MVP to production, act as the primary interface for stakeholders, and mentor engineering teams to maintain delivery velocity and design consistency. Key Responsibilities: - Engage directly with business stakeholders to surface outcome metrics and validate use-case feasibility - Drive rapid prototyping cycles followed by elaboration, design and architecture finalization - Architect enterprise-grade GenAI solutions including RAG, agentic workflows, and human-in-the-loop systems - Lead concurrent delivery of multiple AI use-cases ensuring MVP readiness within 46 weeks - Establish architectural guardrails across data, models, orchestration, and deployment - Ensure compliance with enterprise security, privacy, and governance standards - Translate architecture into delivery plans including backlog, sprint planning, and acceptance criteria - Mentor engineering teams of 10-15 to maintain delivery velocity and design consistency - Own lifecycle from MVP to production including UAT and operational handover - Act as primary interface for stakeholders, articulating trade-offs and value realization Qualifications Required: - 812 years of experience in AI solution architecture or applied AI delivery - Experience delivering AI/GenAI solutions from concept to production - Strong understanding of LLM ecosystems, embeddings, vector databases, and agent frameworks - Experience building scalable AI pipelines with cost, latency, and observability considerations - Ability to manage multiple concurrent deliveries under tight timelines - Solid software engineering fundamentals including CI/CD and infrastructure automation - Working knowledge of cloud AI services - Experience implementing data privacy and governance controls - Ability to translate business problems into structured AI solutions - Strong stakeholder communication and decision-making skills - Knowledge of Agile methodologies as well as experience working with tools like JIRA Role Overview: AI Studio in India is seeking an AI Solution Architect to drive end-to-end ownership of high-impact AI use-cases from problem framing to production deployment. This role operates at the intersection of business-technology outcomes and applied AI, orchestrating rapid prototyping, scalable architecture design, and delivery of parallel MVPs and products across multiple use-cases within compressed timelines. You will engage directly with business stakeholders to surface outcome metrics, drive rapid prototyping cycles, lead concurrent delivery of multiple AI use-cases, and ensure compliance with enterprise security, privacy, and governance standards. Additionally, you will own the lifecycle from MVP to production, act as the primary interface for stakeholders, and mentor engineering teams to maintain delivery velocity and design consistency. Key Responsibilities: - Engage directly with business stakeholders to surface outcome metrics and validate use-case feasibility - Drive rapid prototyping cycles followed by elaboration, design and architecture finalization - Architect enterprise-grade GenAI solutions including RAG, agentic workflows, and human-in-the-loop systems - Lead concurrent delivery of multiple AI use-cases ensuring MVP readiness within 46 weeks - Establish architectural guardrails across data, models, orchestration, and deployment - Ensure compliance with enterprise security, privacy, and governance standards - Translate architecture into delivery plans including backlog, sprint planning, and acceptance criteria - Mentor engineering teams of 10-15 to maintain delivery velocity and design consistency - Own lifecycle from MVP to production including UAT and operational handover - Act as primary interface for stakeholders, articulating trade-offs and value realization Qualifications Required: - 812 years of experience in AI solution architecture or applied AI delivery - Experience delivering AI/GenAI solutions from concept to production - Strong understanding of LLM ecosystems, embeddings, vector databases, and agent frameworks - Experience building scalable AI pipelines with cost, latency, and observability considerations - Ability to manage multiple concurrent deliveries under tight timelines - Solid software engineering fundamentals including CI/CD and infrastructure