Minimum of 6+ years of experience building data‑driven software solutions
Minimum of 3+ years of hands-on AI development experience.
Proficiency in Python, with practical experience building applications using LLMs, embeddings, vector databases, and RAG architecture.
Demonstrated experience with generative AI models, including multimodal models.
Hands-on experience developing and deploying AI applications using Azure Foundry, Docker, Kubernetes, and GPU-backed compute.
Bachelor's degree in computer science, Artificial Intelligence, or a related field, or equivalent professional experience
Experience fine-tuning, evaluating, and deploying models using Azure-managed AI services and compute resources
Familiarity with agent frameworks and experience deploying AI agents with tool integration, appropriate permissions, and operational safeguards
Experience building graph-enhanced RAG and hybrid retrieval solutions using graph databases such as Neo4j, Stardog, or Azure Cosmos DB for Apache Gremlin
Experience deploying models with low latency and high throughput, using frameworks like vLLM and other GPU model deployment tools
Hands-on experience building CI/CD pipelines and automated testing workflows for generative AI application
Experience with distributed training, GPU optimization, and large-scale model frameworks (CUDA, RAPIDS)