AI Engineer

We are seeking an experienced AI Engineer to design, develop, and deploy scalable AI solutions powered by machine learning and large language models (LLMs). The ideal candidate will have hands-on experience building Retrieval-Augmented Generation (RAG) systems, developing end-to-end AI pipelines, and deploying solutions on Microsoft Azure.

Key Responsibilities

• Design, build, and maintain AI and machine learning applications for production environments.
• Develop and optimize Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise knowledge sources.
• Create end-to-end AI pipelines for data ingestion, preprocessing, embedding generation, model inference, evaluation, and monitoring.
• Integrate LLMs and generative AI capabilities into business applications.
• Build scalable APIs and microservices to serve AI models and workflows.
• Deploy, manage, and optimize AI solutions using Azure cloud services.
• Collaborate with data engineers, software developers, product managers, and business stakeholders to deliver AI-driven solutions.
• Monitor model performance, implement feedback loops, and continuously improve system accuracy and reliability.
• Ensure AI solutions meet security, governance, and compliance requirements.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of experience in AI/ML engineering or software engineering.
• Strong proficiency in Python and modern AI frameworks.
• Experience building and deploying RAG-based applications.
• Experience designing AI pipelines and workflow orchestration.
• Hands-on experience with Azure AI services and cloud-native deployments.
• Strong understanding of machine learning, NLP, and generative AI concepts.
• Experience working with REST APIs, Docker, and CI/CD pipelines.

Preferred Qualifications

• Experience with Azure OpenAI Service.
• Experience with Azure AI Search, Azure Machine Learning, Azure Functions, and Azure Kubernetes Service (AKS).
• Knowledge of vector databases such as Pinecone, Weaviate, ChromaDB, or Azure AI Search vector capabilities.
• Experience with LangChain, LlamaIndex, Semantic Kernel, or similar orchestration frameworks.
• Familiarity with MLOps practices, model monitoring, and automated deployment pipelines.
• Experience with enterprise document processing and knowledge management systems.