AI platform strategy
Platforms and services that help teams move from AI experiments to reliable product capabilities.
AI Platform · Enterprise Data · Engineering Leadership
Jiankun Liu
Engineering leader building AI platforms, enterprise data systems, and practical AI products.
I help teams turn fragmented data, tools, and workflows into reliable AI-enabled products. My work sits at the intersection of AI platforms, enterprise data, backend systems, search and retrieval, and engineering execution.
AI Platform
Practical AI systems
Enterprise Data
Governed data access
Platforms
Backend foundations
Leadership
Strategy to execution
Profile
Building the infrastructure layer behind practical AI products.
I am an engineering leader with experience building AI-enabled products, enterprise data platforms, backend systems, search and retrieval capabilities, and applied machine learning workflows. I focus on the infrastructure that makes AI useful in real organizations: data access, retrieval, orchestration, governance, observability, and scalable engineering delivery.
Across my work, I care less about AI demos that look impressive once, and more about systems that teams can operate, integrate, and trust in production.
Venture
Lattivia
Lattivia is an agent capability search and resolution layer for AI workflows. It helps supervisor agents and AI platforms discover, rank, and select the right capability before execution.
The product is built around a simple thesis: as organizations adopt more APIs, MCP servers, tools, workflows, and sub-agents, the hard problem becomes capability resolution — knowing what the agent should use, under what constraints, with what risk and authorization requirements.
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How I create leverage
Enterprise data platforms
Backend and GraphQL platforms that make complex business data accessible, governed, and product-ready.
Engineering leadership
Leading teams through ambiguous platform problems across strategy, architecture, execution, and delivery.
Agentic AI infrastructure
Systems that help agents reason over tools, capabilities, context, and constraints before they act.
Search and retrieval systems
Retrieval systems that turn scattered enterprise knowledge, APIs, and operational data into usable product experiences.
AI product execution
Turning AI concepts into shipped systems with architecture, observability, deployment, and iteration loops.
Perspective
Field notes from building data, AI, and platform systems.
I write about what I have learned building enterprise data platforms, AI-enabled products, search and retrieval systems, and engineering teams. The focus is practical: how ambiguous technology trends become systems that teams can operate, scale, and trust.
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