Data Engineer

Job Description

• Design and consume RESTful APIs for AI services, including generative AI, TTS, STT and NLP.
• Integrate third-party AI APIs (e.g., Azure OpenAI) into enterprise applications.
• Integrate APIs with API Gateway for authentication, rate limiting, and monitoring
• Develop web applications using Next.js
• Integrate frontend with chatbot APIs (Python / Node.js backend)
• Document and maintain API specifications for internal and external use.
• Collaborate with data scientists to deploy trained models into production environments.
• Implement model inference pipelines and monitor performance metrics (latency, accuracy, throughput).
• Design and develop chatbot solutions using Large Language Models (LLMs)
• Implement Retrieval-Augmented Generation (RAG) using knowledge bases
• Design and implement AI agent workflows with multi-step reasoning and decision-making
• Integrate chatbot with internal/external tools via function calling / API orchestration
• Manage conversation context, memory, and state across interactions
• Collaborate with data scientists to deploy trained models into production environments.
• Apply MLOps principles for continuous integration and delivery of AI models.
• Deploy and manage chatbot and AI services on Azure Cloud
• Work with services such as Azure OpenAI, Azure AI Search, App Service, and Storage
• Integrate data pipelines with cloud storage (e.g., Azure Data Lake, Blob Storage) and compute resources.
• Implement CI/CD pipelines, containerization (Docker), and scalable deployment patterns
• Ensure responsible AI practices, including fairness, explainability, and data privacy.
• Contribute to internal knowledge sharing and best practices for applied machine learning.
• Implement secure and scalable cloud architectures for AI model hosting and inference.
• Monitor and optimize cloud resource usage, ensuring cost-efficiency and performance.
• Use Azure DevOps for pipeline automation, model versioning, and release management.

Qualification

• At Least 3 years of experience as an Data Engineer, AI Engineer, Software Engineer, or related field.
• Strong coding skills i.e. Python, NodeJS
• Experience with CI/CD pipelines, Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
• Hands-on experience with Azure Cloud services, especially those related to AI, data science, and DevOps.
• Experience designing and managing data science infrastructure, including compute, storage, and orchestration.
• Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, Azure ML pipelines).
• Effective communication and teamwork to bridge technical and business needs.
• Continuous learning to adapt to evolving Data and AI technologies