Product Owner (AI & Prompt Strategy)

STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India. This role is responsible for defining enterprise prompt strategy, AI personas, and multi-agent orchestration while partnering with cross-functional teams to deliver scalable, secure, and measurable AI capabilities.

STAND 8 provides end-to-end IT solutions to enterprise partners across the United States and with offices in Los Angeles, New York, New Jersey, Atlanta, and more including internationally in Mexico and India.

Experienced Product Owner with a strong background in conversational AI, generative AI, and enterprise voice-agent solutions to lead the strategy, roadmap, and execution of AI-driven customer experiences. This role is responsible for defining enterprise prompt strategy, AI personas, and multi-agent orchestration while partnering with cross-functional teams to deliver scalable, secure, and measurable AI capabilities. The Product Owner will drive business alignment, product prioritization, performance optimization, and continuous improvement through data-driven decision making. This position plays a critical leadership role in advancing enterprise AI initiatives while ensuring operational excellence and exceptional customer experiences.

Location & Work Type

Location: Carrollton, Texas

Work Type: Onsite

Key Responsibilities

• Own the overall product vision and roadmap for enterprise conversational AI and voice-agent initiatives.
• Define and govern the enterprise AI persona, brand voice, system instruction, and prompt development strategy.
• Lead product orchestration across sales, servicing, fulfillment, and operational teams supporting parallel AI-agent development.
• Architect multi-agent conversational models that route user intent to specialized AI agents.
• Define agent responsibilities, context parameters, tool access, decision logic, and escalation paths.
• Develop, test, refine, and optimize system prompts, prompt templates, system instructions, and few-shot examples.
• Balance conversational quality, contextual accuracy, token efficiency, latency, and operational performance across AWS-based AI solutions.
• Establish product frameworks and dashboards to measure prompt effectiveness, AI performance, and customer outcomes.
• Track AI-specific metrics including hallucination rates, contextual accuracy, containment rates, task completion, latency, escalation frequency, and user abandonment.
• Utilize customer feedback and operational metrics to continuously improve AI performance.
• Lead prioritization of business requirements across multiple stakeholder groups.
• Identify dependencies, resolve competing priorities, and eliminate business and technical bottlenecks.
• Define and maintain representative AI evaluation datasets and testing scenarios.
• Partner with engineering teams to integrate automated evaluation pipelines and quality frameworks.
• Lead A/B testing initiatives for prompts, conversational flows, personas, and response strategies.
• Define product success metrics aligned with business KPIs.
• Track Customer Satisfaction, Average Handle Time, containment, conversion, and resolution metrics.
• Collaborate with engineering teams on APIs, infrastructure integration, latency optimization, and AI safety guardrails.
• Mentor Product Analysts responsible for prompt development, testing, business requirements, and knowledge management.
• Present product strategy, roadmap, risks, and performance updates to executive leadership.

Qualifications

Required:

• 5-7 years of experience in Product Management, Product Ownership, AI Product Management, or a comparable product leadership role.
• Demonstrated experience leading conversational AI, voice AI, generative AI, or large language model products.
• Strong knowledge of prompt engineering, including system prompts, system instructions, prompt templates, few-shot examples, context management, and iterative tuning.
• Proven ability to design multi-agent systems, agent-routing models, complex conversational architectures, or state-machine workflows.
• Experience translating complex business rules and operational processes into precise technical configurations and natural-language interaction flows.
• Strong understanding of large language models, retrieval-augmented generation, AI orchestration, vector databases, and automated evaluation methods.
• Experience defining product strategy, roadmaps, success metrics, requirements, user stories, and acceptance criteria for enterprise technology products.
• Strong analytical background with experience developing performance dashboards, evaluating data, and identifying actionable trends.
• Experience planning and executing A/B tests, controlled experiments, or iterative product-optimization initiatives.
• Familiar