Technical Product Manager

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.

 

About The Role

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.

 

Key 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

 

Preferred Qualifications

  • Experience with vector databases and semantic search systems
  • Knowledge of fine-tuning, model optimization, and deployment strategies
  • Familiarity with containerization, CI/CD, and cloud infrastructure (k8s/OpenShift)
  • Experience building or managing SaaS products at scale
  • Background in data science, ML engineering, or applied AI research
  • Track record of shipping GenAI products from concept to production

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