The ideal candidate will have 12-15+ years of software engineering experience and 8+ years of applied AI/ML experience, with a background in architecting and delivering large-scale AI systems and exposure to areas such as large language models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI, orchestration frameworks, MLOps, distributed training, and enterprise AI modernization. Experience with Python, PyTorch, TensorFlow, cloud platforms (AWS, Azure, GCP), and full-stack application development is wanted, and prior work with federal environments, AI governance, cloud-native architectures, DevSecOps, microservices, and managed AI platforms such as AWS Bedrock, Azure OpenAI, and Google Vertex AI is preferred.