Builder Product Manager, AI Platform & Agentic Workflows

Location: Dublin, California, United States

Company

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

What you will do

• Own delivery of customer-facing 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 solutions using the platform, SDK, agents, APIs, and MCP-enabled tools.
• Drive workflows from prototype to production-ready quality and distinguish product gaps, data issues, model behavior, orchestration failures, tool-calling problems, UI gaps, and engineering defects.
• Test end-to-end workflows, reproduce failures, document high-signal bugs, and validate fixes across source code and deployed environments.
• Partner with applied research on datasets, evaluation, training, experimentation, model testing, and structured feedback.

Requirements

• 4+ years of professional experience in product management or product-adjacent technical roles, with a track record of shipping complex platform products end to end.
• Strong technical foundation across software systems, APIs, SDKs, data workflows, AI applications, enterprise platforms, and cloud-based 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 translate ambiguous customer needs into technical requirements and acceptance criteria, test features end to end, troubleshoot issues, reproduce bugs, and provide structured feedback.
• Strong written and verbal communication, documentation, and presentation skills.

Nice to have

• Experience with customer demos, technical product walkthroughs, source-code and repository reviews, and cross-environment validation.
• Experience creating synthetic datasets, evaluation sets, prompt test suites, or domain-specific training examples.
• Experience partnering with researchers, data scientists, ML engineers, or applied AI teams.
• Experience with knowledge graphs, natural-language query systems, agentic copilots, RAG workflows, AI evaluation, or enterprise industry workflows.
• MBA or experience creating product videos and demo walkthroughs.

Culture & Benefits

• Fast-moving environment with evolving customer needs, research priorities, and platform capabilities.
• Culture centered on humility, early feedback, learning from experiments, and measurable outcomes.
• Emphasis on ownership, rigorous review, practical problem-solving, and helping teammates.
• Focus on building AI that delivers meaningful value and supports accuracy, explainability, and auditability in high-stakes environments.