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Roles & Responsibilities -
Define product vision, strategy and roadmap for agentic AI systems.
Translate user pain points into product requirements, user stories, and success metrics.
Lead end-to-end lifecycle for LLM-based products from discovery to iteration.
Establish evaluation frameworks for LLMs and prioritize RAG pipelines, prompt engineering, and validation loops.
Drive integrations with observability, incident management, and deployment systems.
Conduct user research and translate production challenges into roadmap priorities.
Skills/Requirement -
Min 10 years of experience with significant product management exposure.
Experience leading large-scale AI/ML or cloud-based product initiatives.
Strong understanding of LLMs, agentic systems, RAG pipelines, and MLOps.
Ability to engage deeply with engineering teams on technical topics.
Experience working in fast-paced, cross-functional environments.
Strong analytical and data-driven decision-making skills.
Proven ability to influence without direct authority.
Job ID: 150429223
Skills:
Ml, Software Development, Ux, UI, Market Analysis, product lifecycle management, Engineering, Ai, responsible AI principles, Data Research, ethical AI development practices
Skills:
Technical Documentation, Apis, Data Quality, Data Management, Integration patterns, Non-functional requirements, Enterprise technology products, Access controls, Governance, Lineage, Cloud-based platforms, Data AI platforms, entitlements, platform architecture, Analytics enablement, AI ML enablement
Skills:
Sql, data scientists, conversational AI, evaluation frameworks, open-source models, GPT, conversational AI platforms, chatbots, Claude, fine-tuning, LLM GenAI capabilities, AI-powered features, experiment design, analytics dashboards, ML engineers, Dialogflow, Rasa, RAG architectures, prompt engineering
Skills:
Data Quality, Technical Documentation, Data Management, Apis, entitlements, Cloud-based platforms, Non-functional requirements, AI ML enablement, Lineage, Access controls, Governance, platform architecture, Enterprise technology products, Data AI platforms, Analytics enablement, Integration patterns
Skills:
Technical Documentation, Apis, Data Quality, Data Management, Integration patterns, Non-functional requirements, Enterprise technology products, Access controls, Governance, Lineage, Cloud-based platforms, Data AI platforms, entitlements, Analytics enablement, platform architecture, AI ML enablement
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