AI Architect

As an experienced AI/ML Architect, you will be responsible for designing, developing, and implementing scalable Artificial Intelligence and Machine Learning solutions. Your role will involve leading AI strategy, architecting enterprise-grade ML systems, guiding engineering teams, and driving innovation using modern AI technologies such as Generative AI, LLMs, NLP, Computer Vision, and Predictive Analytics. Key Responsibilities: - Design scalable AI/ML system architectures for enterprise applications. - Define end-to-end AI solution strategy and technical roadmap. - Select appropriate AI/ML models, frameworks, and cloud technologies. - Build secure, reliable, and high-performance AI platforms. - Develop and optimize machine learning models and pipelines. - Work on NLP, Computer Vision, Recommendation Systems, Predictive Analytics, and Generative AI use cases. - Design and implement LLM-based applications using OpenAI, Azure AI, Hugging Face, LangChain, etc. - Fine-tune and deploy AI models for production environments. - Design data pipelines for training and inference workloads. - Implement MLOps practices including model monitoring, versioning, CI/CD, and automation. - Ensure model scalability, performance optimization, and governance. - Architect AI solutions on AWS, Azure, or Google Cloud platforms. - Work with Docker, Kubernetes, APIs, and distributed systems. - Ensure data security, compliance, and scalability standards. Qualifications & Skills: - Bachelors/Masters degree in Computer Science, AI, Data Science, or related field. - Relevant AI/ML certifications are a plus. - Experience working on enterprise AI transformation projects. - Strong understanding of AI ethics and responsible AI. - Excellent communication and leadership skills. - Ability to manage multiple projects and stakeholders. - Mentor AI/ML engineers and development teams. - Collaborate with business stakeholders to identify AI opportunities. - Participate in technical discussions, client meetings, and solution presentations. - Drive innovation and best practices within the organization. As an experienced AI/ML Architect, you will be responsible for designing, developing, and implementing scalable Artificial Intelligence and Machine Learning solutions. Your role will involve leading AI strategy, architecting enterprise-grade ML systems, guiding engineering teams, and driving innovation using modern AI technologies such as Generative AI, LLMs, NLP, Computer Vision, and Predictive Analytics. Key Responsibilities: - Design scalable AI/ML system architectures for enterprise applications. - Define end-to-end AI solution strategy and technical roadmap. - Select appropriate AI/ML models, frameworks, and cloud technologies. - Build secure, reliable, and high-performance AI platforms. - Develop and optimize machine learning models and pipelines. - Work on NLP, Computer Vision, Recommendation Systems, Predictive Analytics, and Generative AI use cases. - Design and implement LLM-based applications using OpenAI, Azure AI, Hugging Face, LangChain, etc. - Fine-tune and deploy AI models for production environments. - Design data pipelines for training and inference workloads. - Implement MLOps practices including model monitoring, versioning, CI/CD, and automation. - Ensure model scalability, performance optimization, and governance. - Architect AI solutions on AWS, Azure, or Google Cloud platforms. - Work with Docker, Kubernetes, APIs, and distributed systems. - Ensure data security, compliance, and scalability standards. Qualifications & Skills: - Bachelors/Masters degree in Computer Science, AI, Data Science, or related field. - Relevant AI/ML certifications are a plus. - Experience working on enterprise AI transformation projects. - Strong understanding of AI ethics and responsible AI. - Excellent communication and leadership skills. - Ability to manage multiple projects and stakeholders. - Mentor AI/ML engineers and development teams. - Collaborate with business stakeholders to identify AI opportunities. - Participate in technical discussions, client meetings, and solution presentations. - Drive innovation and best practices within the organization.