AI Solution Architect (42929)

Join an enterprise-scale AI initiative focused on building standardized AI platforms and scaling GenAI solutions from POC through MVP to fully operational enterprise deployments. As an AI Solution Architect, you will be responsible for designing distributed AI systems, reusable architectural patterns and multi-layer integrations while supporting architectural governance and risk management. The ideal candidate brings hands-on experience with LLM-based solutions, RAG architectures, vector databases, semantic search systems, agentic workflows and modular architecture design, combined with a strong background in Python AI technologies.

🚀 Project
- working on a large-scale international GenAI transformation program
- delivering 100+ GenAI use cases across multiple industries
- supporting parallel delivery pods with multiple teams running simultaneously
- driving the transition from POC to MVP and fully scaled enterprise solutions
- contributing to the development of a standardized AI platform
- designing end-to-end AI architectures covering data ingestion, ETL pipelines, vector databases, RAG layer, LLM orchestration and UI where applicable
- translating business requirements into implementable technical solution designs
- designing scalable and reusable agents, integration patterns and modular architectural components
- reviewing solution designs created by other teams
- ensuring architectural consistency and quality across multiple pods
- supporting feasibility assessments and risk management activities
- evaluating delivery feasibility, technological risks and potential dead ends
- guiding and coordinating multiple teams simultaneously
- making architectural decisions for enterprise-scale AI solutions

🎯 Skills
- 4–10 years of experience in AI architecture or AI engineering
- hands-on experience with LLM-based applications
- production experience with RAG architectures
- experience with vector databases and semantic search systems
- experience designing agentic workflows (multi-agent orchestration)
- strong Python AI ecosystem background (LangChain, LangGraph, or similar)
- ability to design modular architectures
- experience designing distributed AI systems
- system decomposition and modular design skills
- experience with multi-layer system integration
- scalability planning capabilities
- ability to identify and mitigate technical risks
- English at C1 level

💡 Nice to have
- experience in large-scale AI programs with multiple parallel teams
- experience collaborating across time zones, especially U.S.
- experience contributing to architectural standards or communities of practice
- experience transitioning from rapid prototyping to enterprise-standard AI platforms