I’ve spent close to two decades working across large engineering and delivery environments, from enterprise software programs to today’s AI evaluation and GenAI workflows.
Most of my work has centered around scaling complex delivery environments without losing quality, stability, or operational clarity. Over the years, I’ve worked across multi-vendor ecosystems, high-pressure delivery programs, and globally distributed engineering teams where execution quality matters far more than presentation.
My focus today is on AI workflow delivery across areas like RLHF, benchmark evaluation, GenAI engineering, red teaming, coding evaluation, multilingual AI programs, and MLOps support.
At AquSag, we support teams working across technical review environments that require contributors who can operate comfortably inside QA-heavy and engineering-adjacent workflows rather than general annotation setups.
A large part of the work now sits at the intersection of engineering, evaluation, and AI operations, especially as model quality expectations continue rising.
Always happy to connect with people building serious AI programs, evaluation systems, and high-complexity delivery environments.
