Technical Product Manager

Description 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