AI Product Manager

About the role

Unframe is an AI-first startup helping the world's largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping customers move from idea to deployed AI systems faster than anyone else in the market. Backed by Bessemer, Craft, and TLV Partners with $100M in Series B funding, we're building a fast-growing, revenue-generating company working with Fortune 500 customers globally As an AI Product Manager on our team, you'll work directly with customers and internal teams to define, scope, and deliver AI-powered solutions using Unframe's platform. You'll bridge product thinking with real-world use cases, enabling fast, reliable delivery of custom solutions built on a shared core. We work on-site from our Tel Aviv office, collaborating closely across engineering, product, and AI to move fast and build with purpose. This is an opportunity to work with top-tier global customers and solve real, high-impact problems.

Responsibilities

• Translate customer problems into structured solution plans using Unframe.ai's platform
• Own the delivery of end-to-end projects in collaboration with engineers and AI specialists.
• Write detailed specs and define prompt/context structures for solution logic.
• Prioritize requirements and manage tradeoffs across speed, stability, and scope.
• Work closely with the Platform team to surface reusable product patterns.
• Serve as the voice of the user - from enterprise operators to domain experts.

Requirements

• 4+ years of experience in product management or technical delivery roles.
• Experience working closely with engineering teams and technical products.
• Ability to manage complex projects with multiple moving parts.
• Strong written communication, systems thinking, and attention to detail.
• Fluent English speaker - written and verbal communication must be excellent.
• Comfortable working in fast-paced environments with evolving requirements.
• Background in enterprise software, AI tools, or internal platforms.
• Familiarity with prompt engineering, LLMs, or component-based systems.
• Experience working with customers in finance, cybersecurity, or operations.

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