The Senior AI Engineer for this global workflow product plays a specialized role at the intersection of reverse engineering and forward-looking product development. Unlike standard AI roles, this position focuses heavily on "unlocking" decades of tribal knowledge and operational data hidden in legacy silos to power the next generation of AI-driven automation.
You will lead the technical strategy for extracting, mining, and transforming massive volumes of legacy data into high-quality training sets for AI models. Your mission is to evolve our global workflow product from a reactive IT tool into a proactive, AI-driven platform capable of predictive maintenance, anomaly detection, and automated decision-making.
Key Responsibilities
- Legacy Data Mining: Architect and implement advanced data mining techniques to extract valuable operational insights from structured and unstructured legacy systems (e.g., old SQL procedures, mainframe logs, siloed documentation).
- AI Product Evolution: Design and deploy production-ready ML/Deep Learning models that drive core product features such as intelligent workflow routing, natural language interfaces (LLMs), and predictive analytics.
- Feature Engineering for Workflows: Lead the discovery and creation of "features" from legacy data that specifically improve IT workflow efficiency, such as identifying bottleneck patterns or predicting system failures.
- Global Model Management: Oversee the deployment and lifecycle (MLOps) of models across global regions, ensuring low-latency performance and compliance with regional data residency laws (e.g., GDPR, SOC2).
- Reverse Engineering via GenAI: Utilize Generative AI and LLMs to automate the modernization of legacy codebases, turning outdated scripts into documented, cloud-native services.
- Cross-Functional Leadership: Mentor junior engineers and collaborate with Product Managers to translate legacy business logic into modern, AI-powered user experiences