Technical Product Manager

We’re looking for a Technical Product Manager to lead the development and evolution of our enterprise AI products.

You’ll work at the intersection of product strategy and AI/ML engineering, defining product requirements, guiding technical implementation, and ensuring our GenAI solutions deliver measurable business value.

Why Join us?:

Shape the future of enterprise AI products where technical depth meets strategic vision.

Drive product direction for cutting-edge GenAI/ML solutions, bridge the gap between complex AI technologies and business value, and own end-to-end product outcomes in a flat-structured startup environment with high impact and growth potential.

Responsibilities:

• Define and drive product roadmap for GenAI/ML features and capabilities
• Translate complex AI/ML concepts and architectures into clear product requirements and user stories
• Design and specify RAG pipelines, multi-agent orchestration workflows, and LLM-based features
• Collaborate with engineering teams on LLM architectures, prompt design strategies, and model evaluation frameworks
• Establish evaluation criteria and observability frameworks for AI outputs (accuracy, grounding, toxicity, feedback loops)
• Work hands-on with prototyping tools (LangChain, LlamaIndex, Semantic Kernel) to validate concepts and guide implementation
• Partner with stakeholders to align AI/ML capabilities with business objectives and user needs
• Analyze code, schemas, and technical documentation to inform product decisions

Requirements:

• 3+ years of product management experience, preferably in B2B/enterprise software
• 1+ years of hands-on experience in GenAI/ML domains
• Solid understanding of GenAI/ML principles, including LLM architectures, prompt design, RAG pipelines, and multi-agent orchestration
• Familiarity with cloud AI platforms (Vertex AI, AWS Bedrock) and their managed services
• Hands-on experience or prototyping with LLM tooling such as LangChain, LlamaIndex, or Semantic Kernel, including building retrieval or orchestration workflows
• Exposure to evaluation and observability frameworks for AI (output evaluation, feedback loops, response grounding, toxicity, and accuracy testing)
• Ability to read and understand code (Python, SQL, JSON schema)
• R&D background or experience working closely with research teams
• Strong communication and stakeholder management skills, with proven ability to translate complex AI/ML concepts for business and engineering audiences