𝗖𝗼𝗿𝗲 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 (𝗠𝘂𝘀𝘁-𝗛𝗮𝘃𝗲)

5+ Years of strong hands-on experience in AI Engineering, focusing on Large Language Models (LLMs)

Experience building applications using modern LLM frameworks such as LangChain, LangGraph, or similar

Hands-on experience with multi-modal AI agents (e.g., vision + text models like GPT / Claude)

Strong expertise in prompt engineering, agent design patterns (memory, planning, reflection)

Experience with fine-tuning / LoRA techniques for custom AI models

Knowledge of vector databases and semantic search architectures

Experience integrating structured and unstructured data for advanced query and visualization use cases

Hands-on experience with LLM evaluation frameworks (LLM-as-judge, human evaluations)

Experience working with workflow automation tools such as n8n or similar

Exposure to Copilot Studio, Agent Development Kit (ADK), or similar AI development platforms

Strong experience with Git-based version control for managing AI workflows and experimentation

Ability to design, build, and deploy scalable AI-driven applications

Strong problem-solving skills with the ability to work in fast-evolving AI environments

𝗣𝗿𝗲𝗳𝗲𝗿𝗿𝗲𝗱 / 𝗚𝗼𝗼𝗱 𝘁𝗼 𝗛𝗮𝘃𝗲

Experience working on enterprise AI solutions or production-grade LLM applications

Exposure to data visualization and analytics-driven AI use cases

Familiarity with cloud platforms supporting AI workloads

Strong understanding of AI ethics, governance, and responsible AI practices

Strong stakeholder communication and documentation skills