About the Role
The Solution Architect designs AI-driven, LLM‑based technical solutions across multiple pods. This role is responsible for interpreting business requirements, shaping the architectural approach, and ensuring that solutions follow emerging standards-while moving quickly enough to support the high-volume demand.Expectations:- 4-10 years experience in architecting or engineering AI‑powered systems:- LLM-based applications- Retrieval‑augmented generation (RAG)- Vector databases- Agentic workflows- Python-based AI stacks (LangChain, LangGraph, etc.)- Ability to design flexible and modular architectures, not monolithic products.- Experience reviewing and validating multi-component solutions (data ingestion, ETL, AI layer, UI/UX where needed).Soft Skills- Strong problem-solving mindset with ability to propose pragmatic solutions quickly.- Comfortable working across time zones with U.S. architects and partners.- Curious, collaborative, and willing to share learnings in a community-of-practice setting.- Ability to support multiple pods simultaneously with consistent quality.- High technical credibility and ability to challenge & guide developers.Key taska:- Design end-to-end architectures for GenAI/LLM-based solutions across 100 use cases.- Review requirements & business architecture documents and translate them into actionable solution designs.- Collaborate closely with TPMs and engineering teams to guide implementation, troubleshoot risks, and ensure alignment.- Create scalable, repeatable solution patterns, allowing reuse of components across pods and industries. (E.g., reusable release‑management agents across SAP/Oracle/Guidewire.)- Balance speed over formality early on, while gradually contributing to future standardization across teams.- Support multi-shipment planning, contributing to feasibility assessments (POC -> MVP).- Participate in an architecture guild/committee as standards mature.