AI & Generative AI Product Architect (Chicago)
Centraprise, Chicago, IL, United States
AI & Generative AI Product Architect
Chicago, IL
Fulltime (Permanent)
Job Description:
Experience Required: 10–12 years
Core Skills: AI/GenAI Product Management: End-to-end product lifecycle, roadmap, scaling. Generative AI Solutions: Copilots, conversational AI, summarization, agent-based systems. LLM & AI Engineering: Model selection, prompt engineering, fine-tuning coordination. AI Platforms & LLMOps: Azure OpenAI, GenAI platforms, pipelines, deployment. Responsible AI & Governance: Security, compliance, human-in-the-loop validation. Reusable Frameworks: Accelerators, toolkits, reusable AI components. Business Translation: Converting use cases into scalable AI capabilities. Integration: Embedding GenAI into enterprise analytics and engineering systems.
Key Responsibilities: Own end-to-end AI/GenAI product lifecycle (ideation → deployment → scaling). Define product roadmap, KPIs, and adoption metrics. Design and deliver GenAI-powered tools (copilots, agents, automation solutions). Collaborate with data science & engineering teams on models and evaluation frameworks. Drive LLMOps and platformization using enterprise cloud (Azure preferred). Build reusable AI frameworks and accelerators for faster delivery. Ensure Responsible AI, security, and compliance adherence. Integrate AI solutions into existing enterprise products and workflows.
Job Description:
Experience Required: 10–12 years
Core Skills: AI/GenAI Product Management: End-to-end product lifecycle, roadmap, scaling. Generative AI Solutions: Copilots, conversational AI, summarization, agent-based systems. LLM & AI Engineering: Model selection, prompt engineering, fine-tuning coordination. AI Platforms & LLMOps: Azure OpenAI, GenAI platforms, pipelines, deployment. Responsible AI & Governance: Security, compliance, human-in-the-loop validation. Reusable Frameworks: Accelerators, toolkits, reusable AI components. Business Translation: Converting use cases into scalable AI capabilities. Integration: Embedding GenAI into enterprise analytics and engineering systems.
Key Responsibilities: Own end-to-end AI/GenAI product lifecycle (ideation → deployment → scaling). Define product roadmap, KPIs, and adoption metrics. Design and deliver GenAI-powered tools (copilots, agents, automation solutions). Collaborate with data science & engineering teams on models and evaluation frameworks. Drive LLMOps and platformization using enterprise cloud (Azure preferred). Build reusable AI frameworks and accelerators for faster delivery. Ensure Responsible AI, security, and compliance adherence. Integrate AI solutions into existing enterprise products and workflows.