Description

Design, implement, and optimize generative AI architectures and agentic workflows using Python.

This role is on-site.

Responsibilities

• Build agentic AI solutions using LLMs, including tool/function calling, memory, and orchestration.
• Develop retrieval-augmented generation (RAG) pipelines to improve factuality and response quality.
• Integrate AI models into production environments for scalable, reliable deployments.
• Collaborate with data scientists to collect, preprocess, and manage large datasets with strong quality controls.
• Optimize machine learning models for training, evaluation, and production performance.

Required Skills

• 5+ years of relevant experience in AI/ML engineering.
• Proficiency in Python for end-to-end AI/ML engineering and model implementation.
• Experience with Generative AI and LLM-based solution development.
• Strong understanding of Machine Learning fundamentals, including training and evaluation.
• Practical experience implementing Retrieval-Augmented Generation (RAG).
• Ability to design and optimize generative AI architectures.
• Degree in computer science, artificial intelligence, IT, or equivalent.

Preferred Skills

• Experience with cloud-based platforms such as AWS, Azure, or GCP for scalable AI deployments.

Key Skills

Education

Any Graduate