Advanced Modeling: Apply dimensional modeling (Kimball/Inmon) to ensure data structures reflect actual business processes, making them intuitive for AI models and analysts alike.
Mentor junior AI engineers, set best practices for prompt engineering, RAG pipelines, and agent evaluation, and help build reusable AI infrastructure for the broader team.
Integrate enterprise applications through authenticated APIs and MCP where appropriate, selecting deterministic workflows, agents or conventional ML based on the problem.
You will own production reliability through observability, service-level targets, incident improvement and mandatory participation in on-call rotations.
Build document-processing and information-extraction solutions for structured and unstructured data, supporting enterprise needs across multiple departments.
SME for QC Micro - Operational readiness (Eg: Environment, Utilities and Product test), infrastructure/instrumentation needs and compliance readiness (Eg: Track & Trend) against cGMP/EHS/Regulatory compliance expectations to global/site procedures.
Build Source Channels — Develop YouTube and LinkedIn as strategic channels for both organic discovery and AI-search visibility. Work with content and video freelancers to create, distribute, and optimise content that compounds over time.
Solution and proposal development: Translate requirements into solution concepts, PoC scope, work plans, assumptions, risks and proposal content; coordinate inputs from architects, engineers, data specialists and partners.
Collaborate closely with business stakeholders, data scientists, engineers, and IT teams to translate business requirements into technical AI solutions.
Act as a subject matter expert in the development of business outcomes using AWS methodologies, tool suite selection, and design and methodology execution