Product Owner (AI & Prompt Strategy)

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Location: Dallas, TX (hybrid)

Job Description

We are seeking a Product Owner (AI & Prompt Strategy) to serve as a prompt-development focused leader for conversational AI initiatives. Operating within a Federated Hub-and-Spoke model, you will sit at the orchestration level across work teams to own the company-wide prompt and persona strategy. Partnering closely with the core engineering team and leading a team of Product Analysts, you will drive the parallel development and deployment of voice AI agents across CDL/Sales, Servicing, and Fulfillment.

Key Responsibilities:

· Strategy & Orchestration: Lead the overall product vision for conversational AI agents, owning the company-wide persona, brand voice, and overarching prompt strategy.

· Agent & Sub-Agent Architecture Design: Architect the multi-agent orchestration layer, defining how primary routing agents interpret user intent and seamlessly hand off tasks to specialized, domain-specific sub-agents (e.g., specific agents for Sales vs. Servicing vs. Fulfillment). Establish the logic boundaries, tool access, and context parameters for each sub-agent.

· Iterative Prompt Refinement: Continuously develop, test, and tune complex system prompts, system instructions, and few-shot examples. Optimize these prompts across the AWS tech stack to balance conversational quality, token efficiency, and response latency.

· Prompt Effectiveness Tracking & Analytics: Establish robust tracking frameworks to measure prompt and agent efficacy at a granular level. Monitor specialized metrics such as hallucination rates, contextual accuracy, task completion/containment rates, and user drop-off to drive continuous prompt optimization cycles.

· Stakeholder Alignment: Serve as the central orchestrator across CDL/Sales, Servicing, and Fulfillment teams to negotiate and refine business requirements, ensuring parallel development without technical bottlenecks.

· Testing & Quality Assurance: Define the "Golden Dataset" of test scenarios to feed into engineering’s automated LLM-as-a-judge evaluation pipelines. Oversee structured A/B testing initiatives and data analysis to iteratively optimize agent responses against baseline configurations.

· Performance & ROI: Define product strategy and track ROI by aligning AI agent performance to key business KPIs, including Customer Satisfaction (CSAT) and Average Handle Time (AHT).

· Cross-Functional Collaboration: Partner with the engineering team to integrate prompt designs with the core infrastructure, latency management pipelines, and real-time safety guardrails.

What You’ll Bring

· 5–7 years of Product Management or Product Ownership experience, ideally within mortgage, fintech, or complex customer servicing environments.

· Demonstrated experience with AI/ML products, specifically conversational AI, Large Language Models (LLMs), and deep prompt engineering strategies within an enterprise AWS environment.

· Proven ability to design multi-agent or complex state-machine conversational architectures.

· Strong analytical background with a track record of building effectiveness dashboards, running A/B tests, and utilizing AI-specific metrics (e.g., hallucination tracking, prompt latency) to drive improvements.

· Ability to translate complex business logic into precise technical configurations and natural language flows.

· Exceptional leadership and stakeholder management skills.

Kaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, spouse of protected veteran, or disability.