Principal AI Product Manager (AI Strategy & Platforms)

TL;DR

Principal AI Product Manager (AI Strategy & Platforms): Strategically architecting hirify.global's internal AI transformation, moving from fragmented "Shadow AI" to a unified, secure Enterprise Agent Fabric with an accent on AI adoption, ethics, and investment. Focus on defining requirements for a centralized orchestration layer and ensuring AI frameworks are built on high-fidelity data.

Location: Based in Ireland with the ability to sync daily with US Central/East Coast hours.

Company

hirify.global empowers companies and agencies of all sizes to build, power, manage, and optimize their WordPress websites and applications with confidence.

What you will do

• Steer the internal AI Council, acting as a high-visibility advisor to the C-suite.
• Define the requirements for a centralised orchestration layer, ensuring AI agents can securely access core systems.
• Lead the "Buy vs. Build" strategy, evaluating native AI features against custom RAG-based solutions.
• Ensure AI frameworks are built on high-fidelity data, moving from fragmented "Shadow AI" to a governed Internal AI Gateway.
• Translate complex concepts like LLMOps and Token Economics into high-impact business narratives.

Requirements

• 7-10+ years in Product Management, specifically in Enterprise Platforms, Data Products, or Systems Architecture.
• Deep AI/ML & Data Mastery: A functional understanding of how generative AI tools, LLMs, and RAG work, and the critical importance of data hygiene.
• Integration Literacy: Deep understanding of MuleSoft (or similar middleware) as the connectivity tissue for AI agents.
• Governance Strength: Proven track record of leading AI ethics, responsible AI, and data governance.
• Executive Presence: Ability to partner closely across business functions (Sales, Marketing, Finance, Legal) and influence C-Suite stakeholders.
• Location: Based in Ireland with the ability to sync daily with US Central/East Coast hours.
• Middleware & Integration: Deep understanding of MuleSoft as the connectivity tissue for AI agents to interact with enterprise systems.
• Data Engineering Literacy: Familiarity with ETL/ELT processes, data warehousing (Snowflake), and BI tools. Ability to define data "cleanliness" standards for LLM consumption.
• The GenAI Stack: Familiarity with orchestration frameworks (LangChain, LlamaIndex), Vector Databases, and Model Evaluation frameworks (Ragas, TruLens).

Nice to have

• Familiarity with orchestration frameworks (LangChain, LlamaIndex) and Vector Databases.
• Hands-on experience with Model Evaluation frameworks (Ragas, TruLens).
• Experience with "Native AI" evaluations (Salesforce Einstein, Zendesk AI, etc.).
• Familiarity with Snowflake and BI toolsets.

Culture & Benefits

• Company Stock Options.
• Great Health Benefits (Medical, Dental, Fertility).
• Generous Vacation Time.
• Pension, 5% company match.
• On-going education through LinkedIn Learning, Workday Learning and our Career Growth Portal.