**About the Role:** We are seeking an experienced **AI Engineer** who brings together the best of **data analytics, cloud computing, and scalable AI application development**. You will be responsible for designing, developing, and deploying AI solutions that leverage real\-time data pipelines, APIs, and containerized microservices. **Key Responsibilities:** * Develop, deploy, and maintain **AI/ML models** and pipelines in production environments. * Build and manage **FastAPI**\-based APIs to serve AI models and analytics results. * Design scalable and secure cloud\-based architectures for AI services (AWS/Azure/GCP). * Containerize applications using **Docker** and orchestrate with **Kubernetes**. * Collaborate with data scientists, backend engineers, and DevOps teams to integrate models into applications. * Optimize data ingestion, preprocessing, and model inference pipelines for performance and reliability. * Monitor and improve model accuracy and system performance post\-deployment. **Required Skills \& Qualifications:** * Bachelor's or Master’s degree in Computer Science, AI/ML, Data Engineering, or related field. * 3\+ years of experience in AI/ML engineering or backend data systems. * Proficient in Python with experience in **FastAPI**, NumPy, pandas, and ML libraries (scikit\-learn, PyTorch, or TensorFlow). * Strong understanding of **cloud services** (AWS/GCP/Azure) and deployment best practices. * Hands\-on experience with **Docker** and **Kubernetes** for scalable service orchestration. * Solid background in **data analytics**, including ETL, big data processing, and model interpretation. * Familiarity with CI/CD tools and MLOps frameworks is a plus. **Nice to Have:** * Experience with real\-time data pipelines (Kafka, Spark Streaming, etc.) * Knowledge of database systems (SQL and NoSQL) * Exposure to monitoring tools like Prometheus, Grafana, or ELK stack * Prior experience working with edge AI or distributed ML environments Job Type: Full\-time Pay: ₹15,773\.05 \- ₹52,938\.83 per month Work Location: In person