As an AI Software Engineer, you will be actively involved with the full software and machine learning lifecycle. You will be expected to support requirements analysis, conduct trade studies for model and framework selection, present AI design architectures, and implement solutions utilizing techniques like Retrieval-Augmented Generation (RAG) and model training or fine-tuning.
Solutions will be created from established requirements using robust engineering processes tailored for AI in production systems. This process will guide the selection, development, and evaluation of foundational models, AI agent platforms, and orchestration frameworks. Additionally, you must be able to independently complete detailed design and development work for individual AI components, establishing robust agent context and memory management capabilities.
Once individually developed, these components must seamlessly integrate into the broader products, frequently requiring integration with vector databases at the subsystem level. Following strict software and ML engineering standards is crucial for building reliable systems, particularly when applying advanced logic like reinforcement learning techniques. Comprehensive documentation of model behavior, integration points, and system architecture is expected throughout the entire effort.
You must also maintain a clear understanding of the project schedule and budget, ensuring all tasks-from initial model evaluation to production deployment-stay on track. Finally, as a senior member of the team, you may be responsible for providing technical oversight on AI integration to the broader development team and communicating directly with the customer to ensure AI capabilities align with their operational needs.