Centraprise
AI/ Generative AI Architect
₹ Check with seller / month
✓ Actively Hiring
📍 Chicago
💼 Full Time
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Job at a Glance
- Category
- IT Engineer & Developer
- Location
- Chicago, Illinois, United States
- Salary
- Check with seller
- Job Type
- Full Time
- Company
- Centraprise
- Status
- Open & Active
Job Description
AI/ Generative AI Architect
Chicago, IL
Fulltime (Permanent)
Job Description:
Experience Required: 10–12 years
Core Skills:
• AI / Generative AI Architecture: GenAI solution architecture, enterprise AI platforms, AI product engineering, scalable AI systems.
• LLM & GenAI Technologies: Large Language Models (LLMs), copilots, conversational AI, intelligent automation, summarization engines, agent-based AI solutions.
• AI Product Management: Product lifecycle management, AI product strategy, roadmap planning, KPI definition, value realization metrics.
• Prompt Engineering & Model Optimization: Prompt strategies, model evaluation, fine-tuning coordination, AI testing frameworks.
• Cloud & Platform Engineering: Azure AI services, Azure OpenAI, GenAI playgrounds, LLMOps, MLOps pipelines, cloud-native AI deployment.
• AI Governance & Responsible AI: AI governance, Responsible AI, compliance, security, legal controls, human-in-the-loop validation.
• Frameworks & Accelerators: Reusable AI frameworks, accelerators, toolkits, enterprise AI enablement.
• Cross-Functional Collaboration: Stakeholder management, engineering collaboration, data science coordination, business alignment.
Key Responsibilities:
• Own the complete lifecycle of AI and GenAI products from ideation through deployment and scaling.
• Translate business use cases into scalable and enterprise-grade AI product capabilities.
• Define product roadmaps, adoption metrics, business KPIs, and value realization measures.
• Design and enable GenAI-powered products including copilots, conversational AI, automation engines, and agentic solutions.
• Collaborate with engineering and data science teams on model selection, fine-tuning, prompting, and evaluation strategies.
• Build reusable GenAI frameworks, accelerators, and enterprise toolkits for faster implementation.
• Partner with cloud/platform teams to deploy AI solutions using Azure-based GenAI and LLMOps platforms.
• Ensure compliance with Responsible AI, governance, security, and enterprise regulatory standards.
Chicago, IL
Fulltime (Permanent)
Job Description:
Experience Required: 10–12 years
Core Skills:
• AI / Generative AI Architecture: GenAI solution architecture, enterprise AI platforms, AI product engineering, scalable AI systems.
• LLM & GenAI Technologies: Large Language Models (LLMs), copilots, conversational AI, intelligent automation, summarization engines, agent-based AI solutions.
• AI Product Management: Product lifecycle management, AI product strategy, roadmap planning, KPI definition, value realization metrics.
• Prompt Engineering & Model Optimization: Prompt strategies, model evaluation, fine-tuning coordination, AI testing frameworks.
• Cloud & Platform Engineering: Azure AI services, Azure OpenAI, GenAI playgrounds, LLMOps, MLOps pipelines, cloud-native AI deployment.
• AI Governance & Responsible AI: AI governance, Responsible AI, compliance, security, legal controls, human-in-the-loop validation.
• Frameworks & Accelerators: Reusable AI frameworks, accelerators, toolkits, enterprise AI enablement.
• Cross-Functional Collaboration: Stakeholder management, engineering collaboration, data science coordination, business alignment.
Key Responsibilities:
• Own the complete lifecycle of AI and GenAI products from ideation through deployment and scaling.
• Translate business use cases into scalable and enterprise-grade AI product capabilities.
• Define product roadmaps, adoption metrics, business KPIs, and value realization measures.
• Design and enable GenAI-powered products including copilots, conversational AI, automation engines, and agentic solutions.
• Collaborate with engineering and data science teams on model selection, fine-tuning, prompting, and evaluation strategies.
• Build reusable GenAI frameworks, accelerators, and enterprise toolkits for faster implementation.
• Partner with cloud/platform teams to deploy AI solutions using Azure-based GenAI and LLMOps platforms.
• Ensure compliance with Responsible AI, governance, security, and enterprise regulatory standards.
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