AI Product Manager

About Us

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

About The Role

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.

What You’ll Do

• 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.
  
  

• 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.