AI Product Manager
Listed on 2026-06-05
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IT/Tech
AI Engineer (Applied/Software), Data Analyst
Remote (US-Based)
· Optional hybrid in New York, NY
Locked In AI is the #1 real-time AI interview and meeting copilot, trusted by over one million users worldwide. We are a fast-growing company building the most advanced career preparation platform on the market.
Our platform delivers real-time, AI-powered assistance during live job interviews, coding assessments, and professional meetings — helping candidates communicate with clarity, confidence, and competence.
Role OverviewWe are looking for a strategic, user-obsessed AI Product Manager to own the vision, roadmap, and execution of AI-powered features and products at Locked In AI. This is a high-ownership role — you will define what we build, why we build it, and how we measure success.
You will bridge the gap between cutting-edge AI capabilities and real user needs, turning complex technology into intuitive product experiences for over 1 million users. Your scope spans the full product lifecycle — from identifying opportunities and defining requirements, to working with engineering and data science teams to ship AI features, to analyzing post-launch performance and iterating based on real-world data.
The ideal AI Product Manager understands both the possibilities and limitations of AI. You know when a problem calls for an LLM, when it calls for a simpler rule-based approach, and when the best solution is better UX, not more AI. You are data-driven, deeply empathetic to user needs, and relentless about shipping products that move the needle.
Key Responsibilities- Define and own the product vision and strategy for Locked In AI’s AI-powered features, ensuring alignment with company objectives, market opportunities, and user needs
- Develop and maintain a prioritized product roadmap that balances short-term wins with long-term strategic bets — making tough tradeoffs between business value, user impact, and technical feasibility
- Conduct ongoing market research, competitive analysis, and user research to identify opportunities where AI can create differentiated value for job seekers and professionals
- Translate high-level business goals into clear, actionable product requirements and success metrics that engineering, data science, and design teams can execute against
- Lead the end-to-end product development lifecycle for AI features — from discovery and ideation through design, development, testing, launch, and iteration
- Collaborate closely with engineering, data science, and research teams to define AI feature specifications, ensuring requirements account for model capabilities, data dependencies, latency constraints, and edge cases
- Work with design and UX teams to translate complex AI functionality into intuitive, trustworthy user experiences — managing the unique challenges of probabilistic, non-deterministic AI outputs
- Coordinate cross-functional execution across engineering, design, QA, marketing, and operations to ship AI features on time and with high quality
- Drive a deep understanding of user needs, pain points, and behaviors through qualitative research (interviews, usability tests, support tickets) and quantitative analysis (product analytics, behavioral data)
- Define and run experiments (A/B tests, feature rollouts, holdback tests) to validate hypotheses, measure feature impact, and make data-driven product decisions
- Build and maintain feedback loops that capture user reactions to AI features — including satisfaction signals, error reports, and feature requests — and translate them into prioritized improvements
- Champion a culture of continuous experimentation, ensuring every major AI feature has a clear measurement plan and success criteria before launch
- Define KPIs and success metrics for every AI feature — including model accuracy, response quality, latency, user engagement, retention, and business impact
- Monitor AI product performance post-launch, identifying quality regressions, user experience issues, and opportunities for optimization
- Collaborate with data and analytics teams to build dashboards and…
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