Senior Product Manager, AI
New
J
JobgetherCommercial Real Estate
Based in United StatesFull-TimeSenior
Salary150,000 - 170,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- Product ManagementPrompt EngineeringLLM
Requirements
- 5+ years of experience in product management, including experience launching AI/ML or LLM-powered features used by real customers.
- Proven experience owning product strategy, roadmaps, and execution in fast-paced technology environments.
- Hands-on experience with rapid prototyping tools such as Claude, Cursor, Replit, or similar platforms.
- Strong understanding of prompt engineering, context design, retrieval-augmented generation (RAG), and practical LLM capabilities.
- Experience conducting customer discovery, user interviews, workflow analysis, and translating insights into product priorities.
- Ability to collaborate effectively with engineering and design teams to build high-quality software products.
- Technical depth to discuss tradeoffs involving models, data, infrastructure, latency, and product quality.
- Strong analytical mindset with experience defining success metrics and using evidence to guide decisions.
- Excellent communication skills, with the ability to explain complex technical concepts to both technical and business audiences.
- Comfortable operating independently in ambiguous environments and making thoughtful decisions with incomplete information.
Responsibilities
- Define the AI product vision, strategy, and roadmap, determining which capabilities to build, prioritize, and scale.
- Work directly with customers to understand workflows, validate assumptions, test AI capabilities, and translate insights into product decisions.
- Partner closely with engineering and design teams to deliver AI-powered features from concept through launch and ongoing improvement.
- Create and maintain evaluation frameworks, quality benchmarks, and success criteria for AI features.
- Determine when to use deterministic systems versus LLM-based approaches to deliver the most accurate and reliable user experiences.
- Design and improve prompts, retrieval strategies, context management, and AI workflows using measurable results.
- Establish AI safety and reliability standards, including grounding strategies, permission controls, and hallucination prevention.
- Monitor product and AI performance metrics, including adoption, task success, accuracy, reliability, latency, and cost efficiency.
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