AI Engineer - Python/PySpark

Description :AI Engineer (LLM & Advanced AI)

Experience Range : 3 9 Years

Location : Bangalore/Hyderabad (Open to Pan India)

Employment Type : Full-Time

Role Overview :

We are looking for a skilled AI Engineer with strong experience in AI/ML engineering, LLM systems, and production-grade AI deployments. The ideal candidate will have hands-on expertise in advanced AI architectures, model validation, MLOps, and cloud-native deployments.

This role requires a strong engineering mindset with the ability to design scalable AI systems and deliver business value, preferably within the Insurance & Reinsurance domain.

Key Responsibilities :

• AI/ML Engineering :

• Design, develop, and deploy AI/ML models in production environments.

• Apply advanced analytics and data science techniques to validate AI models.

• Build scalable data pipelines using Python, PySpark, and SQL.

• Work with large enterprise datasets using distributed computing frameworks (Spark/Hadoop/Hive).

• LLM & Advanced AI Capabilities :

• Implement and optimize LLM-based applications.

• Perform prompt engineering, prompt testing, and lifecycle management.

• Design and deploy RAG (Retrieval-Augmented Generation) architectures.

• Implement AI orchestration frameworks and agentic workflows.

• Develop tool/function calling mechanisms and AI agents.

• Ensure performance monitoring and evaluation of generative AI systems.

• MLOps & Model Governance :

• Implement model evaluation, calibration, and performance monitoring.

• Ensure model explainability, fairness, and robustness.

• Set up CI/CD pipelines for ML models.

• Deploy models with logging, monitoring, and alerting frameworks.

• Work with MLOps tools for versioning, experimentation tracking, and governance.

• Cloud & Platform Engineering :

• Deploy AI solutions on AWS, Azure, or GCP.

• Integrate AI models into production systems.

• Build and manage scalable cloud-native AI infrastructure.

• Ensure reliability, scalability, and security of deployed solutions.

• Engineering & Delivery :

• Work in Agile/Scrum environments.

• Participate in sprint planning, story estimation, and DevOps processes.