Senior Software Engineer, AI

What You Will Do

• Design develop and deploy AI-powered applications leveraging Generative AI Large Language Models (LLMs) Computer Vision Machine Learning and Agentic AI technologies.
• Build scalable backend services APIs and workflow orchestration components for AI solutions.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines intelligent assistants and workflow automation solutions.
• Develop Computer Vision and OCR solutions for image analysis document digitization information extraction and automation workflows.
• Train optimize evaluate and deploy machine learning and deep learning models for production use.
• Build data pipelines supporting AI model training validation and inference workflows.
• Develop cloud-native AI applications and deploy solutions on Azure and other cloud platforms.
• Implement MLOps best practices including model versioning monitoring CI/CD and deployment automation.
• Collaborate with cross-functional teams to translate business and clinical requirements into scalable AI solutions.
• Create technical documentation architecture diagrams validation reports and deployment artifacts.
• Stay current with advancements in AI Computer Vision LLMs and Agentic AI.

What You Will Need

Required Qualifications

• Bachelors Degree in Computer Science Artificial Intelligence Machine Learning Data Science Software Engineering Electrical Engineering or a related field with 3 years of relevant industry experience; OR
• Masters Degree in Computer Science Artificial Intelligence Machine Learning Data Science Software Engineering Electrical Engineering or a related field.
• Strong programming skills in Python.
• Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Experience developing APIs backend services and distributed applications.
• Familiarity with Computer Vision techniques including OCR image classification segmentation and object detection.
• Understanding of LLMs Prompt Engineering Retrieval-Augmented Generation (RAG) and Agentic AI concepts.
• Experience working with structured and unstructured data and building data pipelines.
• Experience with cloud platforms such as Azure AWS or GCP.
• Knowledge of databases version control systems CI/CD pipelines and software development best practices.
• Familiarity with Docker Kubernetes and MLOps concepts.

Preferred Qualifications

• Experience with Azure AI Services Azure OpenAI Azure Machine Learning or similar AI platforms.
• Experience with LangChain LangGraph Semantic Kernel AutoGen or equivalent AI frameworks.
• Experience building production-grade GenAI RAG OCR or intelligent document processing solutions.
• Experience with MLflow monitoring tools and model lifecycle management.
• Exposure to healthcare medical imaging or regulated environments.
• Experience creating technical architecture documentation and contributing to solution design discussions.