Generative AI & LLMs: Hands-on experience building production LLM applications and designing agentic systems: prompt and context engineering, retrieval-augmented generation (including graph-based retrieval), tool use, state and control flow design, orchestration frameworks, and the tracing, guardrails, and evaluations that make them reliable. Basic knowledge of fine-tuning, parameter-efficient adaptation, dataset construction, and evaluation.
Real, practical exposure to using GenAI / LLMs / coding assistants in delivery – beyond experimentation, with an understanding of enterprise governance.
Design specialized prompts and system instructions for AI agents, enabling them to perform multi-step reasoning, tool-use, and autonomous task execution
Validate workflows and outputs, improve accuracy, reliability and efficiency based on user feedback, and maintain practical workflow documentation and user guides.
Challenge and influence engineering decisions related to tooling design, manufacturing processes, automation strategies, inspection methods, process controls, and production scalability.
Solution Development & Communication: Lead teams to identify opportunities, develop proposals and secure new business; oversee scope, resources and delivery of key projects, communicating solution value clearly.
Solution Development & Communication: Support requirements gathering, solution preparation and documentation under project guidance, communicating findings clearly to technical and non-technical stakeholders.
Production Engineering: Translate messy, real-world financial records (invoices, bank statements, contracts, ledgers) into structured data via OCR, NLP, and agentic workflows.