AI Architect/ Senior AI Engineer_ LLMOps

Required Qualifications: 6-10 years of experience in working on ML projects that includes business requirement gathering, model development, training, deployment at scale and monitoring model performance for production use casesStrong knowledge on Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional)Should have worked on proprietary and open-source large language modelsExperience on LLM fine tuning, creating distilled model from hosted LLMsBuilding data pipelines for model trainingExperience on model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observabilityExperience in GenAI application deployment on cloud and on-premises at scale for productionExperience in creating CI/CD pipelinesWorking knowledge on KubernetesExperience in minimum one cloud: AWS / GCP / Azure to deploy AI servicesExperience in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGenExperience in light weight UI development using streamlit or chainlit (optional)Desired experience on open-source tools for ML development, deployment, observability, and integrationBackground on DevOps and MLOps will be a plusExperience working on collaborative code versioning tools like GitHub/GitLabTeam player with good communication and presentation skills Required Qualifications: 6-10 years of experience in working on ML projects that includes business requirement gathering, model development, training, deployment at scale and monitoring model performance for production use casesStrong knowledge on Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional)Should have worked on proprietary and open-source large language modelsExperience on LLM fine tuning, creating distilled model from hosted LLMsBuilding data pipelines for model trainingExperience on model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observabilityExperience in GenAI application deployment on cloud and on-premises at scale for productionExperience in creating CI/CD pipelinesWorking knowledge on KubernetesExperience in minimum one cloud: AWS / GCP / Azure to deploy AI servicesExperience in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGenExperience in light weight UI development using streamlit or chainlit (optional)Desired experience on open-source tools for ML development, deployment, observability, and integrationBackground on DevOps and MLOps will be a plusExperience working on collaborative code versioning tools like GitHub/GitLabTeam player with good communication and presentation skills