Azure AI Platform Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced Azure AI Platform Engineer to design, develop, and deploy advanced AI/ML and Generative AI solutions across enterprise environments. This role focuses on GenAI, ModelOps, LLM frameworks, and scalable AI platform engineering., * Design and develop AI/ML solutions including:
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Prediction, recommendation systems
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NLP, computer vision, and conversational AI (bots)
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Build and deploy Generative AI solutions using modern LLM frameworks
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Work on RAG (Retrieval-Augmented Generation) and agent-based architectures
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Develop scalable backend services using:
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Python (Flask, Django, FastAPI)
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Leverage ML frameworks:
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TensorFlow, PyTorch, Keras, Scikit-learn, SpaCy
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Utilize LLM ecosystems:
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Hugging Face, embedding models, vector databases
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Work with cloud AI platforms:
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Azure OpenAI, Google Vertex AI, AWS AI/ML services
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Build and maintain data pipelines and AI infrastructure
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Collaborate with cross-functional teams to deliver AI use cases and POCs
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Communicate complex technical concepts to business stakeholders
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Conduct training and mentor teams on AI/ML best practices
Requirements
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7+ years of experience in:
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Azure architecture
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Azure Kubernetes Services (AKS)
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3+ years of experience in:
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AI Platform Engineering / ModelOps
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Strong expertise in:
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Python and ML ecosystem
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Deep learning, NLP, GANs, and generative models
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Experience with:
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RAG frameworks and LLM-based architectures
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LLM APIs, embeddings, vector databases
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Hands-on with:
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CI/CD and scalable ML deployment
Preferred Skills
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Experience with:
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Azure OpenAI, Google Vertex AI, AWS AI services
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Transformers (BERT, PaLM, etc.)
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Strong statistical and analytical background
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Experience in enterprise/banking environments
Important Notes
- Mandatory hybrid work (3 days onsite/week)
- Candidate must be open to Atlanta, Dallas, or Charlotte locations
- Strong preference for candidates with enterprise/banking domain experience
