Product Owner / Product Manager

Role: Product Owner/Product Manager

Location: Atlanta, GA (Hybrid from Day 1)

Duration: 12 Months

Job Description:

Product Owner / Product Manager Conversational AI (Voice) for Healthcare Payer Call Center Virtual Assistants

Role Summary

We are seeking a Product Owner / Product Manager to lead strategy and delivery of voice-based Conversational AI for call center virtual assistants in a healthcare payer environment.

You will own the roadmap and execution for an AI-driven voice experience that improves containment, reduces handle time, increases first-call resolution, and elevates member/provider satisfaction while meeting regulatory and privacy requirements (HIPAA/PHI).

This role requires hands-on product fluency in LLMs, speech-to-text (ASR/STT), text-to-speech (TTS), and increasingly speech-to-speech and real-time voice agent architectures. Key

Responsibilities

Product Strategy & Roadmap

Own product vision and roadmap for a voice virtual assistant supporting payer call center intents (benefits, claims status, eligibility, prior auth status, ID card, pharmacy benefits, find care/provider).

Prioritize initiatives across containment/deflection, intelligent routing, authentication, and agent handoff with context transfer.

Build business cases using contact center KPIs and measurable ROI.

LLM & AI Product Leadership

Define where and how to use LLMs safely and effectively (e.g., intent understanding, entity extraction, summarization, guided dialog, knowledge Q&A via RAG).

Drive implementation choices and guardrails: RAG vs fine-tuning vs prompt-only approaches Tool/function calling patterns to complete transactions (claims lookups, benefit checks) Grounding, citation/traceability patterns (where required), and hallucination mitigation

Establish evaluation methods for LLM features (offline test sets online monitoring), including quality, safety, and latency targets.

Speech/Voice Technology Ownership (STT, TTS, Speech-to-Speech)

Partner with engineering/ML to define and optimize the voice stack: STT/ASR accuracy targets (WER), domain vocabulary tuning (payer terminology, drug names, provider names), noise handling, barge-in behavior TTS voice quality, prosody, pronunciation dictionaries, multilingual considerations (if applicable)

Speech-to-speech / real-time voice agents: latency budgets, streaming audio, turn-taking, interruption handling, and naturalness

Own requirements for low-latency voice interactions and establish SLAs (e.g., time-to-first-response, end-to-end turn latency).

Discovery, Requirements & Delivery

Translate payer workflows into conversational capabilities with clear user stories, and acceptance criteria.

Lead cross-functional delivery with engineering, data science, conversational design, QA, analytics, security, and vendor partners.

Drive integration with contact center platforms (e.g., Genesys, Amazon Connect) and core payer systems (CRM, claims, eligibility, provider data, prior auth).

Compliance, Privacy & Risk

Ensure HIPAA/PHI-compliant design: data minimization, secure handling, retention policies, audit logs, redaction, and access controls.

Define escalation and safe-completion patterns for sensitive scenarios (grievances/appeals, clinical-like questions, potential vulnerability).

Partner with Compliance/Legal on user disclosures, consent, and governance for generative experiences.

Measurement & Continuous Improvement

Own KPIs and monitoring: Containment/deflection, AHT impact, transfer rate/quality, task completion, CSAT STT: WER, no-match rates, latency NLU/LLM: intent accuracy, entity accuracy, grounded answer rate, safety flags, fallback rate

Establish an ongoing tuning program: utterance expansion, prompt/knowledge updates, pronunciation and language model updates, regression testing.

Required Qualifications

5 years in Product Management/Product Ownership, with 2 years in Conversational AI / voice bots / IVR modernization.

Strong healthcare payer experience (member/provider services; benefits, claims, eligibility, authorizations).

Demonstrated product experience with: LLMs

Business Analysis

Agile