Artificial Intelligence Engineer

Role Purpose / Summary: **

As a Senior AI/ML Engineer, you will be at the core of the Brio AI Factory, responsible for the hands-on development, training, and deployment of advanced artificial intelligence and machine learning models. You will implement the technical vision set by the Solutions Architect, building the high-performance AI components that power large-scale use cases and drive innovation.

Key Responsibilities: **

• Develop, train, and fine-tune advanced AI/ML models, including LLMs, VLLMs, and SLMs, for

specific project requirements.

• Implement complex retrieval-augmented generation (RAG) systems, leveraging both knowledge

bases and graph data structures.

• Design and implement sophisticated prompts and agentic AI workflows to create intelligent,

autonomous systems.

• Write clean, production-grade Python code for model development, data processing, and API

creation.

• Collaborate closely with Data Engineers to build and optimize data pipelines for model training

and inference.

• Work with DevOps Engineers to containerize (Docker), deploy (Kubernetes), and monitor models

within a CI/CD and MLOps framework.

• Participate actively in an agile team, contributing to sprint planning, daily scrums, and code

reviews to ensure timely delivery of high-quality AI features.

Required Technical Skills: **

• Expertise in Visual Large Language Models (VLLMs), Large Language Models (LLMs), and Small

Language Models (SLMs).

• Deep understanding and practical experience with Knowledge RAG and Graph RAG patterns.

• Advanced skills in Prompt Engineering, Model Fine-tuning, and Model Distillation.

• Proficiency with Vector Databases (e.g., Pinecone, Milvus) and Graph Databases (e.g., Neo4j).

• Experience in designing and building Agentic AI Models and multi-agent systems.

Preferred Skills / Tools / Frameworks: **

• Proficiency with core Python data science libraries (e.g., Pandas, NumPy, Scikit-learn).

• Experience with deep learning frameworks such as PyTorch or TensorFlow.

• Familiarity with AI/ML platforms and tools on Azure (Azure Machine Learning, Azure OpenAI).

• Experience with MLOps tools like MLflow for model tracking and lifecycle management.

Experience Level: **

• 7 to 9 years in a hands-on software engineering or data science role, with a primary focus on

building and deploying AI/ML models.

Education: **

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field. A

Master's degree is preferred.