My path started in enterprise SaaS and customer workflows, then moved into AI implementation as the practical bridge between messy operations and usable systems.
I have 10 years across enterprise SaaS, healthcare GTM, technical scoping, multi-stakeholder customer work, and practical AI-assisted workflow building.
The common thread is operator translation: understanding the people, constraints, handoffs, and trust gaps that decide whether a system actually gets used.
AI-assisted building became useful because it let me turn that workflow judgment into prototypes, QA loops, and proof artifacts faster.
Start with the Interview Proof Pack, then read the proof pages that match the role. The case studies show how I define problems, guide AI-assisted implementation, validate outputs, and support adoption.
The coding-heavy work is framed accurately as AI-assisted build support, not a traditional software engineering claim.
Recruiters should use the recruiter fit page before sending a LinkedIn message.