AI Architect

As an experienced AI Architect, your role will involve leading the design, development, and deployment of large-scale AI solutions. You will be responsible for bridging the gap between business requirements and technical implementation, with a focus on generative AI and modern MLOps practices. Key Responsibilities: - Architect end-to-end AI systems utilizing large language models and generative AI technologies - Design scalable, production-ready AI applications that align with business objectives and performance requirements - Evaluate and integrate LLM APIs from leading providers such as OpenAI, Anthropic Claude, and Google Gemini - Establish best practices for prompt engineering, model selection, and AI system optimization - Fine-tune open-source models like Llama and Mistral for specific business use cases - Implement custom training pipelines and evaluation frameworks - Optimize model performance, latency, and cost for production environments - Stay updated with the latest model architectures and fine-tuning techniques - Deploy and manage AI models at an 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 deployment - Ensure high availability, security, and performance of AI systems in production - Collaborate with stakeholders to understand business problems and translate them into technical requirements - Provide technical guidance and mentorship to development teams - Conduct feasibility assessments and technical due diligence for AI initiatives - Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: - 7+ years of experience in machine learning engineering or data science - Proven track record of delivering large-scale ML solutions Technical 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 services Core 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 - Strong problem-solving skills and architectural thinking Preferred Qualifications: - Experience with vector databases and retrieval-augmented generation (RAG) systems - Knowledge of distributed training and model parallelization techniques - Experience with model quantization and optimization for edge deployment - Familiarity with AI safety, alignment, and responsible AI practices - Experience in specific domains (finance, healthcare, legal, etc.) - Advanced degree in Computer Science, AI/ML, or related field,