Senior AI/ML Engineer
Role summary
Seeking a Senior AI/ML Engineer with expert-level Python skills to design, develop, and deploy advanced AI solutions. The role focuses on LLMs, RAG architectures, and agentic AI systems, requiring deep knowledge of NLP, prompt engineering, and vector databases. Candidates must have 7+ years of experience in Python, Microsoft Azure (including Azure Machine Learning), DevOps, MongoDB, and CI/CD pipelines. Responsibilities include building and optimizing LLM-based systems, integrating AI models into enterprise applications, implementing vector search, and establishing monitoring frameworks for AI systems within a cloud environment.
Job Description:
We are seeking a highly skilled Senior AI/ML Engineer to design, develop, and deploy advanced AI solutions leveraging LLMs, RAG architectures, and agentic AI systems.The ideal candidate will have deep Python expertise, strong NLP knowledge, and hands-on experience integrating AI models into scalable, production-grade cloud environments
Essential Skills:
Azure Machine Learning (ML) - 7+ years
DevOps - 7+ years
Microsoft Azure - 7+ years
Mongo DB - 7+ years
Python - 7+ years
Qualifications:
Expert-level proficiency in PythonStrong experience with LLM integration and RAG architecturesHands-on experience with Prompt/Context EngineeringSolid understanding of NLP concepts and transformer-based modelsExperience with Vector DBs and/or MongoDBKnowledge of CI/CD pipelines and cloud deployment (Azure preferred)Must Have:7+ years of Python experience with expert-level proficiency7+ years of Microsoft Azure experience, including cloud deployment and Azure Machine Learning7+ years of MongoDB experienceHands-on experience with LLM integration and RAG (Retrieval-Augmented Generation) architectures7+ years of DevOps experience, including CI/CD pipelinesFamiliarity with Agentic AI workflows and tool/function callingExperience with observability, monitoring, and evaluation frameworks for AI systems
Roles & Responsibilities:
Design and implement AI/ML solutions using Python and modern ML frameworksDevelop and optimize Prompt Engineering strategies for LLM-based systemsBuild and deploy Retrieval-Augmented Generation (RAG) pipelinesIntegrate LLMs via APIs (Azure OpenAI preferred) into enterprise applicationsDevelop and orchestrate Agentic AI workflows with tool/function callingImplement vector search solutions using Vector DatabasesEnsure CI/CD integration and cloud deployment (Azure preferred)Establish observability, monitoring, and evaluation frameworks for AI systemsCollaborate with cross-functional teams to deliver production-ready AI features
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