Description

You will design and implement AI solutions for enterprise deployment, owning the end-to-end lifecycle from data engineering to model operations.

This role is on-site.

Responsibilities

• Design and implement deployment strategies for AI applications at enterprise scale.
• Build and maintain data engineering pipelines using PySpark and advanced SQL.
• Orchestrate workflows with Airflow and manage containerized services via Kubernetes.
• Deploy and monitor models using MLflow or equivalent cloud-native services.
• Apply Generative AI concepts, including LLMs, prompt engineering, and LangChain.

Required Skills

• 3-5 years of hands-on experience in Data Engineering, Cloud, and DevOps.
• Proficiency in PySpark and Advanced SQL for data processing.
• Experience with cloud services and microservices architecture.
• Knowledge of DevOps practices and CI/CD pipelines.
• Familiarity with Airflow or equivalent orchestration tools.
• Understanding of Kubernetes or cloud-native container services.
• Basic knowledge of Generative AI, LLMs, and Prompt Engineering.

Preferred Skills

• Experience with MLflow for model deployment and monitoring.
• Understanding of Responsible AI principles and performance optimization.

Key Skills

Education

Bachelor's degree