Enterprise AI Architect (Principal / Expert)
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Summary
Senior architect who designs enterprise AI/ML solutions end to end: defining data and integration architecture across complex corporate systems and deploying production-scale AI built on LLMs, RAG, embeddings, and vector databases, with attention to security, privacy, and model-risk governance in regulated settings.
Requirements (Must-have):
- Experience: Minimum 5–8 years of experience in software, data, or machine learning engineering, including at least 3 years in an Architecture or Technical Design Authority role.
- Production AI/ML Practice: Proven hands-on track record of designing and deploying AI/ML systems running at scale in production.
- Domain Expertise: Deep practical knowledge of large language models (LLMs), RAG (Retrieval-Augmented Generation), embeddings, vector databases, and context engineering.
- Enterprise Integration: Experience designing data and integration architecture across complex, heterogeneous enterprise systems.
- Security & Governance: Exposure to regulated environments and understanding of security, data privacy, and model risk review frameworks.
Nice-to-have:
- Experience in FinTech, banking, or other high-volume transactional environments.
- Recognized cloud or architecture certifications (e.g., TOGAF, AWS/Azure/GCP Solutions Architect).
- Postgraduate qualification (Master's or Ph.D.) in a technical discipline (Computer Science, Data Science, Mathematics, or a related field).