Manage the end-to-end MES system enhancement lifecycle, including user requirement gathering, solution discussion, vendor coordination, UAT, deployment, go-live, post-deployment support, change management, and relevant technical documentation.
Architect and lead enterprise-scale AI, GenAI and Agentic AI solutions across Knowledge Management, Data Engineering, Data Management and Application Development use cases, from solution design and PoC/MVP through implementation to production.
Designing, building and shipping LLM-powered features such as assistants, agents, retrieval augmented generation (RAG) and document understanding into our core products.
Bachelor’s degree in information systems, computer science, business analytics, statistics, finance, or a related field; equivalent experience may be considered
System Development: Architect, develop, and deploy scalable AI-powered applications and agentic systems using Python. You'll be expected to leverage your expertise to make smart, fast decisions that align with our product vision.