Join the Technical Product Management team - where you’ll work with great people, pioneering the future of AI-driven products, intelligent workflows, and next-generation decisioning systems.
What Youll Bring
What you’ll bring:
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/prototyping with LLM tooling such as LangChain, LlamaIndex, or Semantic Kernel, including experience 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 & understand code is a plus (e.g., Python, SQL, JSON schema).
Strong communication and stakeholder management skills, with the ability to translate complex AI/ML concepts for business and engineering audiences.
5–8 years of product management experience, with at least 1-2 years in GenAI, ML domains.
A collaborative mindset and passion for productionizing, innovating & improving AI products grounded in reliability, explainability, transparency, and user trust.
Impact Youll Make
Product Vision & Strategy: Define and maintain the roadmap for GenAI -driven platform features within OneTru, focusing on scalable, secure, and explainable AI solutions.
Customer Discovery: Work closely with stakeholders to uncover high-impact use cases, distill pain points, and frame scalable AI-driven solutions.
Cross-Team Collaboration: Partner with AI/ML engineers, data scientists, and platform teams to deliver customer-centric capabilities
Metrics & Evaluation: Define success metrics and evaluation frameworks for LLM-based tools. Champion rapid iteration and continuous improvement loops.
Platform Translation: Act as a bridge between technical and non-technical stakeholders, ensuring all AI capabilities ladder up to customer value and OneTru’s broader business objectives.
Governance & Guardrails: Support responsible AI practices by defining clear boundaries, auditing mechanisms, and evaluation policies.
Experience Guidelines
5-8 years of product management experience, with 1-2 years directly responsible for ML or GenAI features.
Hands-on experience with RAG pipelines, LangChain etc
Familiarity with embedding stores, or knowledge graph integrations, AI agents, MCP servers, model evaluation systems
Experience in prompt engineering, evaluation frameworks, and rapid iteration methodologies.
Experience with data-driven prioritization, and outcome-oriented roadmaps.
This is a hybrid position and involves regular performance of job responsibilities virtually as well as in-person at an assigned TU office location for a minimum of two days a week.
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