Senior Product Manager, AI Products
New
Remote-friendly work environment within eligible U.S. statesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5–7+ years of product management experience, including at least 2+ years working directly on AI-driven products
- Required Skills
- PythonArtificial IntelligenceJavascriptProduct ManagementPrototypingPrompt Engineering
Requirements
- 5–7+ years of product management experience, including at least 2+ years working directly on AI-driven products
- Strong hands-on technical ability, including experience building prototypes or writing production-level or near-production code
- Proven track record of shipping 0→1 products and leading products from concept to launch
- Deep familiarity with AI systems such as LLMs, embeddings, RAG architectures, and evaluation methodologies
- Strong understanding of probabilistic system behavior, including hallucination risks, latency, and cost trade-offs
- Demonstrated ability to independently build prototypes using Python, JavaScript, or similar tools and AI APIs
- Excellent product judgment with the ability to distinguish user value from novelty and prioritize effectively
- Strong execution mindset with the ability to break down complex problems, ship quickly, and iterate based on real-world usage
- Ability to work cross-functionally with engineering, design, and data teams in high-autonomy environments
- Evidence of a builder mindset through side projects, prototypes, or independently shipped tools
Responsibilities
- Lead end-to-end development of AI-native products from discovery through scaling, including user research, prototyping, and production delivery
- Identify and validate high-impact AI opportunities, translating user problems into scalable product solutions
- Build and iterate early prototypes using LLMs, APIs, scripts, and lightweight code to test hypotheses quickly
- Define interaction models, UX flows, and system architecture in close partnership with engineering and design teams
- Design and implement AI evaluation frameworks, including offline and online metrics, feedback loops, and monitoring systems
- Drive experimentation with prompt design, RAG systems, and model iteration cycles to improve product performance over time
- Ship incremental product releases and take full ownership of outcomes, including business and user impact metrics
- Collaborate on data instrumentation, cost optimization, and system scalability across AI-powered features
- Influence product strategy by connecting initiatives to business value, revenue impact, and long-term scalability
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