AI Architect

5 - 7 years

16 - 20 Lacs

Posted:22 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

We are seeking an experienced AI Architect to lead the design, development, and deployment of large-scale AI solutions.
The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices.Key Responsibilities :


AI Solution Design & Implementation :


- Architect end-to-end AI systems leveraging large language models and generative AI technologies- Evaluate and integrate LLM APIs from leading providers (OpenAI, Anthropic Claude, Google Gemini, etc.)- Establish best practices for prompt engineering, model selection, and AI system optimizationModel Development & Fine-tuning :

- Fine-tune open-source models (Llama, Mistral, etc.) for specific business use cases
Infrastructure & Deployment :


- Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes)- Build robust, scalable APIs using FastAPI and similar frameworks- Design and implement MLOps pipelines for model versioning, monitoring, and continuous deploymentMinimum Requirement :


- At least 5+ years of experience in machine learning engineering or data science- At least 1+ years of hands-on experience building, deploying, and managing generative AI models in production- Proven track record of delivering large-scale ML solutionsTechnical Skills :


- Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.)- Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.)- Strong proficiency in FastAPI, Docker, and Kubernetes- Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)- Proficiency in Python and modern software development practices- Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML servicesCore Competencies :


- Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques- Experience with MLOps tools and practices (model versioning, monitoring, CI/CD)- Ability to translate complex business requirements into technical solutions

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