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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and governing domain intelligence layers, including ontology and agent workflow models, while ensuring compliance with standards in PEO and HCM domains. Proficient in developing and fine-tuning AI systems, with a strong focus on model evaluation and deployment in production environments.
Highest-signal resume keywords
Ontology DesignLLM-Based Systems DevelopmentMicrosoft Foundry ExperienceAzure AI WorkloadsPEO and HCM Domain Expertise
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Production Software DevelopmentKnowledge Graph DesignModel Evaluation PipelinesFine-Tuning StrategiesAgent Workflow ModelingDataset Curation StandardsProof-of-Concept DevelopmentDecision Records WritingSemantic Layer DesignMulti-Tenant SaaS Management
Soft Skills
Clear Writing SkillsInfluence Across Team Boundaries
Tools & Technologies
Microsoft FoundryAzureSnowflake Cortex AIMicrosoft Agent Framework
Industry Keywords
PEOHCMPayrollBenefitsSOC 2ISO 27001Regulated-Domain Experience
Tech Stack
Tools & technologiesAzure
About the role
Key responsibilities & impact- Encode PEO and HCM domain meaning so AI capabilities reason correctly about the business
- Own the domain intelligence layer, including ontology, agent workflow models, fine-tuning strategy, and intelligence pattern library
- Build and govern a canonical ontology spanning PrismHR platforms, entities, relationships, business rules, and terminology
- Model business processes as agentic workflows with tool boundaries, decision points, escalation paths, and human-in-the-loop checkpoints
- Define when to fine-tune, retrieve, or rely on prompting
- Establish dataset curation standards for labeling, provenance, retention, and residency
- Develop domain-specific evaluation harnesses for PEO and HCM accuracy
- Build and document retrieval strategies, reasoning templates, agent scaffolds, and validation guards
- Prove patterns through working proof-of-concepts before publishing them as standards
- Engage product teams from design through go-live
- Advise on use-case feasibility and risk
- Act as escalation point for domain-AI design questions
- Contribute to standards conformance decisions and recommendations to the AI Domain Committee
Requirements
What you’ll need- 8+ years building production software, including time at staff, principal, or architect scope where other teams depended on what you owned
- Practical experience designing ontologies, knowledge graphs, or canonical domain models that shipped in production
- Hands-on experience building LLM-based or agentic systems
- Experience with fine-tuning, RAG, or model evaluation pipelines
- Hands-on Microsoft Foundry: model deployment, agent development, and evaluation and safety tooling
- Hands-on Azure, including compute, data, identity, and networking building blocks for AI workloads
- Ability to take a pattern from concept through working proof-of-concept to published standard
- Record of changing technical direction through influence across team boundaries
- Clear writing skills for ontologies, patterns, and decision records
- Preferred: PEO, HCM, payroll, benefits, or adjacent regulated-domain experience
- Preferred: OWL, RDF, SHACL, property graphs, or semantic layer design
- Preferred: Multi-tenant SaaS handling sensitive personal data, including SOC 2 or ISO 27001 environments
- Preferred: Agent frameworks, particularly Microsoft Agent Framework, plus MCP and tool-use orchestration
- Preferred: Snowflake Cortex AI
- Prior AI research experience and formal knowledge-engineering credentials are optional
- Availability Monday to Friday, 3:00 PM–12:00 AM EAT
Benefits
Comp & perks- Health coverage
- Conference and learning support
- Ownership of the layer every AI capability in the company depends on