• Architect and implement GenAI and LLM‑based systems, including fine‑tuning, evaluation, and optimization • Build scalable pipelines for data processing, model training, inference, and continuous improvement • Deploy and manage AI workloads across AWS, Azure, or GCP using cloud‑native services • Integrate embeddings, vector search, and RAG pipelines into production environments • Optimize GPU/accelerator utilization for distributed training and high‑performance inference • Develop automation for CI/CD, MLOps, observability, and model lifecycle management • Ensure cloud security, compliance, and cost‑efficient resource allocation • Evaluate emerging AI frameworks, tools, and cloud services to drive innovation • Partner with cross‑functional teams to translate business needs into technical solutions