Description

You will design and implement agentic systems and LLM architectures on Azure, owning the full lifecycle from data pipelines to production deployment.

This role is on-site.

Responsibilities

• Design and implement agentic systems and multimodal AI agents for real-time decision-making.
• Build, customize, and fine-tune LLMs for NLP, conversational AI, and summarization tasks.
• Architect and maintain complex data pipelines and ETL processes using Azure Data Factory, Synapse Analytics, and Databricks.
• Write scalable Python code and develop reusable libraries for machine learning and data engineering workflows.
• Mentor junior engineers and collaborate with cross-functional teams to drive AI strategic roadmaps.

Required Skills

• 5+ years of experience in machine learning and data engineering roles.
• Azure Certified AI Practitioner certification or equivalent Azure AI/data engineering certification.
• Advanced proficiency in Python and libraries including Pandas, NumPy, PyTorch, TensorFlow, and LangChain.
• Extensive experience building autonomous agentic solutions and orchestration frameworks.
• Hands-on experience with LLM modeling, fine-tuning, prompt engineering, and optimization.
• Deep knowledge of Azure Machine Learning, OpenAI Service, and Cognitive Services.
• Expertise in data engineering practices including schema design, data modeling, and ETL pipeline optimization.
• Proficiency with Databricks, Synapse Analytics, and Azure Data Factory.

Preferred Skills

• Advanced degree (Master’s or PhD) in Computer Science, Data Engineering, or AI/ML.
• Experience deploying LLMs into production for chatbots or document summarization.
• Knowledge of Spark, Hadoop, Docker, Kubernetes, and Git.

Key Skills

Education

Advanced degree (Master’s or PhD) in Computer Science, Data Engineering