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Generative AI and RAG Systems Engineer

Generative AI and RAG Systems Engineer

Brio TechnologiesHyderabad, Republic Of India, IN
24 days ago
Job description

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.

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