We are seeking a highly skilled AI Engineer to design, develop, and deploy scalable AI-powered applications and intelligent automation solutions. The ideal candidate will have strong expertise in Python development, advanced SQL, AI agent workflows, Retrieval-Augmented Generation (RAG) architectures, and data engineering. This role involves building production-grade AI systems, integrating APIs, processing large-scale datasets, and delivering innovative solutions that drive business value.
Required Qualifications
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
3+ years of experience in software development, AI/ML engineering, or a related role.
Strong programming expertise in Python.
Advanced SQL skills with experience in PostgreSQL, SQL Server, or MySQL.
Hands-on experience building AI agent workflows and RAG-based solutions using frameworks such as LangChain, n8n, Gemini, or similar technologies.
Experience working with machine learning and data processing libraries including Pandas, NumPy, Scikit-learn, and XGBoost.
Strong understanding of API integration, RESTful services, JSON/CSV data processing, and large-scale data handling.
Experience implementing data validation, data quality, and data transformation processes.
Proficiency with Git and modern software development practices.
Experience building, testing, deploying, and maintaining production-grade AI applications.
Preferred Qualifications
Experience with FastAPI or Flask for application development, automation, and integrations.
Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
Knowledge of cloud platforms including AWS, Azure, or GCP.
Experience with event-driven architectures, messaging systems, and streaming platforms.
Exposure to optimization frameworks such as OR-Tools.
Experience with computer vision solutions using OpenCV.
Key Responsibilities
Design, develop, and maintain AI-powered applications, agent-based workflows, and RAG solutions.
Build scalable data pipelines for ingestion, transformation, and processing of structured and unstructured data.
Integrate internal and external systems through APIs and automation frameworks.
Develop and optimize machine learning models and AI-driven business solutions.
Ensure data quality, reliability, security, and performance across AI systems.
Collaborate with cross-functional teams to define requirements and deliver innovative AI solutions.
Deploy, monitor, and support AI applications in production environments.
Implement best practices for code quality, version control, testing, and documentation.
Evaluate emerging AI technologies and recommend improvements to existing solutions.