Senior AI Product Owner
New
C
CodeRoadAI software
Latin America | 100% RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Advanced English fluency (C1+ spoken and written)
- Experience
- 4+ years of hands-on experience as a Product Owner or Product Manager delivering software products
- Required Skills
- AgileJiraConfluencePrompt Engineering
Requirements
- Have 4+ years of hands-on experience as a Product Owner or Product Manager delivering software products.
- Have direct experience shipping LLM-powered applications, such as AI agents, RAG architectures, document extraction, or conversational AI.
- Understand LLM evaluation methodologies, prompt engineering workflows, guardrail implementations, and observability or telemetry metrics.
- Be able to assess engineering trade-offs involving model selection, data access patterns, vector search, and infrastructure security.
- Have experience in Agile environments using Jira and Confluence to document technical user stories, decision logs, and API or data requirements.
- Have a track record in client-facing consulting or senior stakeholder management.
- Have advanced English fluency (C1+), spoken and written.
- Financial Services or regulated-sector experience is a plus.
- Familiarity with the Azure AI ecosystem and Microsoft enterprise data stack is a plus.
- Exposure to AI orchestration frameworks such as LangChain, LlamaIndex, or AutoGen, and observability tools such as LangSmith, Phoenix, or Arize is a plus.
Responsibilities
- Identify, define, and prioritize AI use cases based on business value, technical feasibility, and data readiness.
- Translate user needs into granular stories with acceptance criteria and edge-case handling.
- Work with business experts to curate evaluation datasets, review agent outputs, monitor hallucination risks, and refine prompts, guardrails, and context retrieval systems.
- Coordinate sprint planning, grooming, and release scoping with engineers and architects.
- Serve as the primary contact for client leadership, run workshops and feature demos, and secure data-privacy and governance sign-offs.
- Manage milestones, track cloud and LLM costs against budget, and maintain a risk register.
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