Work directly with enterprise customers to understand the workflow they want to automate and translate it into clear agent + data architecture on Lyzr.
Map all relevant data sources (SQL, NoSQL, APIs, file systems, SaaS apps, documents) and define how Lyzr agents will read from them without forcing a heavy central semantic layer.
Design fluid intelligence architectures: agentic data pipelines and mini data marts that keep data close to source while still being agent-friendly and governable.
Define lightweight semantic and graph-based models that help Lyzr agents reason over entities, relationships, and business concepts for specific use cases.
Collaborate with Lyzr's product, agent engineering, and customer teams to produce clear architecture artifacts (diagrams, models, integration specs) and ensure robust, secure data access.
Ideal Candidate
812+ years in data architecture / data engineering / analytics architecture, with strong exposure to complex enterprise environments and multiple data technologies.
Hands-on experience with structured and unstructured data, SQL and NoSQL stores, and integrating data via APIs, file systems, and SaaS platforms.
Deep understanding of semantic data modeling and good working knowledge of graph / knowledge graph concepts and when to apply them.
Comfortable in customer-facing roles: can run discovery sessions, whiteboard solutions, and explain data + agent architecture in clear, non-technical language to business leaders.
Pragmatic, systems-thinking mindset: prefers composable, fit-for-purpose data surfaces for agents over big-bang platforms, and is excited to work at the frontier of agentic AI with Lyzr.
