Description

Key Skills: Python, Generative AI, LLMs, RAG, Agentic AI, Azure OpenAI, Databricks, MLflow, PyTorch, TensorFlow, LangFuse, NLP, Vector Databases

Roles & Responsibilities:

• Design, develop, and deploy enterprise-grade Generative AI and Machine Learning solutions.
• Fine-tune, evaluate, and optimize Large Language Models (LLMs) using proprietary datasets.
• Build and enhance RAG (Retrieval-Augmented Generation) architectures using vector databases and semantic search.
• Develop agentic AI systems capable of reasoning, planning, and autonomous interactions.
• Implement AI/ML training, experimentation, deployment, and monitoring pipelines using Databricks and MLflow.
• Integrate AI solutions with Azure services and enterprise platforms.
• Conduct model benchmarking, performance evaluation, and continuous improvement initiatives.
• Develop prompt engineering, observability, and evaluation frameworks using tools such as LangFuse.
• Collaborate with cross-functional teams to deliver scalable and production-ready AI solutions.
• Ensure reliability, security, and operational excellence of deployed AI systems.

Experience Required:

• 8-15 years of software engineering experience with at least 3+ years in AI/ML solutions.
• Strong hands-on expertise in Python, NLP, LLMs, and Generative AI.
• Experience with OpenAI-compatible APIs, Azure OpenAI, and LLM Gateway solutions.
• Deep understanding of RAG architectures, vector databases, and semantic search.
• Experience with Databricks, MLflow, and MLOps practices.
• Proficiency in PyTorch, TensorFlow, and Scikit-Learn.
• Experience building Agentic AI applications and autonomous workflows.
• Knowledge of Azure Document Intelligence, OCR, and Enterprise Search solutions.
• Experience with LangFuse, AI observability, and evaluation frameworks is preferred.
• Exposure to Speech AI, Vision AI, MS SQL, and Azure certifications is an added advantage.

Education: Any Graduation

Key Skills

Education

Any Graduate