[Remote] Principal Product Manager - Auto Safety

Note: The job is a remote job and is open to candidates in USA. Intrado is dedicated to saving lives and protecting communities, helping them prepare for, respond to, and recover from critical events. The Principal Product Manager for Auto Safety will lead the discovery, strategy, delivery, and growth of AI-powered products that enhance emergency communications for connected vehicles and alarm systems.

Responsibilities

• Continuously synthesize voice-of-customer, field feedback, win/loss insights, and operational telemetry to identify the highest-impact problems in connected-vehicle emergency workflows and alarm programs
• Use AI to accelerate discovery—summarizing qualitative research, clustering incident themes, and extracting repeatable patterns from call/incident data (where permitted) to inform opportunities
• Define problem size and success measures using evidence (baseline performance, time studies, error rates, and customer outcomes) and maintain an always-current opportunity backlog
• Define target segments, personas, and end-to-end journeys across telematics providers, auto OEMs, and public safety stakeholders, including the highest-risk moments where AI assistance must be most reliable
• Set product positioning and measurable value narrative (speed, accuracy, workload reduction, and safety outcomes), partnering with Marketing to translate technical capability into customer impact
• Establish an AI product scorecard: offline evaluation (quality/coverage), online metrics (latency, deflection/assist rate), and operational metrics (incident outcomes, handling time), with thresholds for launch and rollback
• Partner with Sales and Finance to shape packaging and commercial readiness for AI-powered capabilities, including value metrics, entitlements, and guardrails appropriate for regulated environments
• Own the end-to-end product lifecycle for Auto Safety AI features—problem framing, requirements, delivery, adoption, and continuous improvement based on real-world performance
• Define what “good” looks like for AI behavior: acceptance criteria that include model/prompt performance, confidence and fallback handling, and human-in-the-loop workflows for safety-critical decisions
• Partner with Engineering and Data/AI to establish the evaluation and iteration loop (test sets, red-teaming, error taxonomy, regression testing), ensuring predictable releases and measurable quality gains
• Drive an experimentation mindset—A/B tests, phased rollouts, and feature flags—to validate value and de-risk changes before broad deployment
• Maintain product artifacts with an AI-aware lens (PRDs, business case inputs, release readiness) and ensure traceability from customer problem to shipped capability and measured outcome
• Lead go-to-market planning with Marketing, Sales, and Customer Success, including launch goals, target accounts, rollout strategy, and intended use and limitations of AI features
• Create enablement assets (pitch, demo narrative, FAQs, objections, and release notes) that explain AI value in customer terms and set expectations for accuracy, latency, and operational fit
• Operate the “AI in production” cadence: monitor quality, latency, failure modes, and user feedback; drive prioritization of fixes and improvements based on real-world performance
• Partner with Product Operations to ensure launch governance, readiness checklists, and cross-functional alignment for pilots, phased rollouts, and incident response
• Ensure product requirements account for data custody, retention, access controls, and auditability for sensitive incident data, recordings, and transcripts
• Embed Responsible AI practices: risk assessment, human oversight, transparency/communication of limitations, and documented mitigation plans for known failure modes
• Partner with InfoSec, Legal, and Operations on privacy and contractual considerations for AI-enabled features and maintain documentation required for regulated customer environments

Skills

• Bachelor's degree in Computer Science, Engineering, Business, or a related field, or equivalent experience
• 7+ years of product management experience owning complex, customer-facing SaaS products in mission-critical environments
• Experience delivering AI/ML-powered capabilities (e.g., decision support, automation assist, or predictive/insight features)
• Demonstrated ability to define AI product quality and measurement (evaluation datasets, error analysis, online/offline metrics)
• Ability to partner effectively with data science/ML engineering teams
• Experience creating AI platforms for the development of requirements, roadmaps, and competitive intelligence
• Strong analytics and experimentation skills (instrumentation, dashboards, A/B testing, cohort analysis)
• Experience working with security, privacy, and compliance stakeholders to ship data- and AI-intensive products with appropriate controls, documentation, and operational processes

Benefits

• Medical, dental, vision, life and disability coverage
• Paid time off
• A 401(k) retirement plan
• Paid parental leave
• Access to a robust library of personal and professional training resources
• Employee discounts
• Critical illness
• Hospital indemnity
• Access to legal support
• Pet insurance
• Identity theft protection
• An EAP (Employee Assistance Program) that includes free mental health resources/support

Company Overview

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