Key Responsibilities

• Design and implement AI applications using Python, Langchain, RAG, and agentic AI frameworks.
• Craft sophisticated prompt engineering strategies to maximize model performance and user experience
• Integrate AI capabilities into existing business workflows and applications
• Build specialized CI/CD pipelines for AI model lifecycle management
• Implement containerization (Docker) and orchestration (Kubernetes) for resilient production systems
• Optimize resource utilization and system performance in AI deployments
• Leverage Azure services (Azure ML, Azure Databases) to deploy and scale AI solutions
• Design data pipelines connecting AI systems with SQL/NoSQL databases
• Implement efficient data storage and retrieval patterns for AI applications
• Monitor emerging developments in GenAI, agentic systems, and prompt engineering
• Experiment with novel AI methodologies to enhance solution capabilities
• Contribute to the organization's AI strategy and technological roadmap

Qualifications

• Advanced Python programming with AI/ML libraries
• Demonstrated expertise in prompt engineering and generative AI frameworks.
• Experience implementing DevOps practices for AI systems
• Proficiency with database technologies (SQL/NoSQL)
• Strong foundation in Azure cloud services
• Proven track record deploying AI solutions in production environments
• Experience with TensorFlow, PyTorch, or other ML frameworks
• Knowledge of multi-cloud or hybrid cloud environments
• Understanding of security best practices for AI systems