Teach AI what our business actually means.
PEO and HCM are dense domains. Co-employment, payroll, benefits, workers' compensation, and multi-state compliance carry meaning that a general-purpose model simply does not have. Those domains anchor a family of PrismHR platforms, and your job is to encode that meaning so every AI capability we publish reasons about our domain correctly.
You will join the AI Domain team, which owns the enterprise standards, reference architectures, approved model catalog, and governance safeguards for AI across the company. Within it you own the domain intelligence layer: the ontology, the agent workflow models, the fine-tuning strategy, and the intelligence pattern library that product teams build on. This is a hands-on senior individual contributor role — patterns here are proven through working proof-of-concepts before they become standards, so you will build as much as you write.
Four areas of ownership. The canonical ontology as a semantic layer spanning all PrismHR platforms — entities, relationships, business rules,



and terminology across co-employment, payroll, perks administration, workers' compensation, onboarding, and compliance — built with the product teams who own each data model, and governed as a living artifact. Agent workflow modeling: business processes decomposed into agentic workflows with tool boundaries, decision points, escalation paths, and human-in-the-loop checkpoints, defining where agents may act autonomously and where they must defer, especially around payroll, money movement, and compliance. Fine-tuning strategy: when to fine-tune, when to retrieve, when prompting is enough, with dataset curation standards covering labeling, provenance, retention, and residency, and domain-specific evaluation harnesses that measure accuracy in PEO and HCM rather than on generic benchmarks. And the intelligence pattern library: retrieval strategies, reasoning templates, agent scaffolds, and validation guards, each proven by

📌 AI Domain Architect (Noida)
🏢 Distro
📍 Noida