Builder Product Manager (AI Platform)

Location: Dublin, CA (HQ)

Company

hirify.global provides enterprise GenAI solutions for regulated industries, combining domain-specific models, agentic reasoning, model evaluation, and multimodal understanding.

What you will do

• Own customer-facing delivery of agentic missions, including demos, product updates, technical Q&A, and domain working sessions.
• Translate customer needs into product requirements, acceptance criteria, edge cases, data dependencies, and test scenarios.
• Build prototypes, workflow applications, internal tools, demos, and proof-of-concept experiences using the AI platform, SDK, agents, APIs, and MCP-enabled tools.
• Drive workflows from prototype through production-ready quality and identify platform gaps requiring engineering investment.
• Test end-to-end workflows, reproduce failures, isolate root causes, and validate fixes across environments.
• Collaborate with applied research on datasets, evaluation, experimentation, model testing, and structured feedback.

Requirements

• 4+ years of professional experience in product management or product-adjacent technical roles.
• Track record of shipping complex platform products end-to-end.
• Strong technical foundation in software systems, APIs, SDKs, data workflows, AI applications, enterprise platforms, or cloud systems.
• Hands-on experience building prototypes, workflow applications, demos, internal tools, agentic workflows, or customer proof-of-concepts.
• Familiarity with agents, tool-calling, MCP-style tools, LLM applications, RAG, knowledge systems, and AI copilots.
• Ability to define technical requirements, test features end-to-end, troubleshoot issues, reproduce bugs, and communicate clearly with technical and non-technical stakeholders.

Nice to have

• Experience with customer demos, technical walkthroughs, source-code review, repositories, and validating fixes across branches and environments.
• Experience creating synthetic datasets, evaluation sets, prompt test suites, or domain-specific training examples.
• Experience with knowledge graphs, natural-language query systems, agentic copilots, RAG workflows, or AI evaluation.
• Experience partnering with researchers, data scientists, ML engineers, or applied AI teams.
• Exposure to enterprise domains such as manufacturing, energy, finance, semiconductors, healthcare, supply chain, or industrial operations.

Culture & Benefits

• Outcome-oriented environment focused on shipping results rather than presentations.
• Culture of humility, early feedback, experimentation, and learning from failures.
• Strong ownership and attention to quality in product and technical work.
• Opportunities to mentor interns and collaborate across product, engineering, research, and domain teams.