zorba ai
Website:
zorbaconsulting.in
Job details:
Strong experience in AI/ML and GenAI solution architecture, Conversational AI / Agentic AI / RAG frameworks & expertise in Solution design and enterprise architecture frameworks
We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
- We are looking for an experienced AI Solution Architect with 8+ years of overall IT experience and strong expertise in designing and implementing AI/ML and Generative AI solutions for enterprise environments. The candidate should have hands-on experience in building scalable AI architectures, Conversational AI platforms, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) frameworks.
The ideal candidate should possess deep knowledge of enterprise solution architecture, AI integration patterns, LLM ecosystems, and modern AI application design principles. Experience in designing end-to-end AI platforms, integrating AI services with enterprise applications, and driving AI transformation initiatives is highly preferred.
Key Responsibilities
- Design and architect enterprise-grade AI/ML and Generative AI solutions.
- Build and implement Conversational AI, Agentic AI, and RAG-based applications.
- Define scalable AI architecture patterns, governance, and integration frameworks.
- Work closely with business stakeholders, engineering teams, and data scientists to translate business requirements into AI solutions.
- Evaluate and implement LLMs, vector databases, prompt engineering strategies, and orchestration frameworks.
- Lead AI platform modernization and enterprise AI adoption initiatives.
- Ensure scalability, security, reliability, and performance of AI systems.
- Provide technical leadership, architecture reviews, and best practices for AI implementations.
Required Skills
- Strong experience in AI/ML solution architecture and enterprise application design.
- Expertise in Generative AI, LLMs, Conversational AI, Agentic AI, and RAG frameworks.
- Hands-on experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of vector databases, embeddings, prompt engineering, and fine-tuning concepts.
- Experience with cloud platforms such as AWS, Azure, or GCP for AI deployments.
- Knowledge of enterprise architecture frameworks and microservices-based solution design.
- Proficiency in Python and AI/ML development ecosystems.
- Experience with API integrations, orchestration workflows, and scalable AI deployment models.
Preferred Skills
- Experience with AI governance, responsible AI, and model monitoring.
- Exposure to MLOps and AI deployment pipelines.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, HRMS, or knowledge platforms.
- Strong stakeholder communication and solution consulting experience.
Skills: agentic ai,gen ai,enerprise architect,solution architecture
Click on Apply to know more.