I turn promising models into evaluated, observable, and useful products—from retrieval and agents to the interfaces people rely on.
Build a grounded answer from the strongest evidence.
A focused set of systems explained through the problem, engineering decisions, evaluation method, and measurable result.
A fictional example showing how to present hybrid retrieval, answer evaluation, abstention, and human escalation as one production system.
A fictional computer-vision case study centered on calibration, drift monitoring, edge inference, and a review queue for uncertain predictions.
A fictional agent workflow that demonstrates tool permissions, review checkpoints, structured outputs, and observable failure recovery.
I work where model behavior, backend reliability, product experience, and responsible delivery meet.
Evaluated RAG, agent workflows, structured outputs, guardrails, and model orchestration grounded in product constraints.
Experiment tracking, data quality, serving, observability, and feedback loops that connect model behavior to real outcomes.
APIs, interfaces, and cloud delivery treated as one system—from the first interaction to production telemetry.
A sample career path showing how to connect role progression with concrete ownership. Replace every entry with your real experience.
The full résuméReplace this fictional entry with scope, decisions, and outcomes from your current role—not a duplicate of your résumé bullets.
Use the timeline to show progression: what became harder, what you owned, and how your technical judgment grew.
Link meaningful repositories, explain your contribution, and avoid vanity metrics that do not help a reviewer understand the work.
Use this section for technical writing, research notes, talks, or open-source documentation.
A sample article card for explaining evaluation sets, failure categories, and the engineering decisions that follow.
A second sample showing how writing can demonstrate judgment that a list of technologies cannot.
Use this section to connect the work outside your formal role to the same judgment visible in your case studies.
Use this space for a standout open-source project, research artifact, product, talk, or community contribution.
Example University
2019 — 2021 · Optional distinction or focus
AM I’m open to remote ai engineering roles and interested in teams where AI has to earn trust through evidence.