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AI Engineer in Chennai building production-grade AI systems: scalable APIs, LLM integrations, RAG pipelines, and agentic workflows. Day to day involves writing clean Python, testing, documentation, deployments, and optimization.
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, and RAG; evaluate models and datasets.
Build and deploy production-grade AI systems, including RAG pipelines, agentic workflows, and scalable APIs with Python and cloud-native tools.
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, RAG, and vector databases in Python with PyTorch and HuggingFace.
Build and improve NLP and Generative AI solutions using prompt engineering, fine-tuning, RAG, and evaluation frameworks while collaborating with AI Engineering teams.
Build and tune NLP and generative-AI models using prompt engineering, fine-tuning, RAG, and vector databases, then deploy them with Docker and GPU training.
Design and deploy scalable, real-time AI systems including LLM inference pipelines, RAG, and vector databases using Python, TensorFlow/PyTorch, and Kubernetes.
Lead a team building enterprise-grade full-stack apps with Python/FastAPI backend, React/Angular frontend, and Azure cloud services, while mentoring engineers and owning CI/CD pipelines.
Lead product strategy and delivery for an Agentic AI platform that uses LLMs, ML, RPA, and computer vision to automate enterprise tasks. Day-to-day involves backlog prioritization, roadmap definition, and cross-functional collaboration.
Build and optimize high-performance Python backend systems and agentic AI workflows, using frameworks like LangChain and FastAPI, from prototype to production.
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