BEST-FIT USE CASE
Best fit for AI product initiatives that need a lead who can translate business needs into an MVP, define acceptance criteria, coordinate cross-functional delivery, and guide implementation of LLM, RAG, ASR, evaluation, and analytics workflows.
Not the primary fit: Less aligned with roles focused only on pure model research, mobile development, frontend-only implementation, or infrastructure-only platform ownership.
EVIDENCE HIGHLIGHTS
What supports the assessment
01Owned roadmap, acceptance criteria, UI/UX prototypes, product-market fit validation, and client onboarding for a production speech-analytics platform.
02Designed end-to-end AI solution architecture covering agent orchestration, retrieval, data architecture, asynchronous workflows, and service integration.
03Built evaluation and guardrail workflows using PII stripping, LLM-as-judge hallucination scoring, and latency tracking before release decisions.
04Benchmarked embedding and chunking approaches against a curated evaluation dataset, tracking retrieval quality and latency.
05Evaluated and integrated multiple ASR engines for a speech-to-text call-processing layer.
06Designed and optimized Python ETL pipelines across SQL and NoSQL databases for large post-call analytics datasets.
07Built and scaled BI and NLP analytics capabilities, including tokenization, lemmatization, and dashboard integration.
08Earlier analytics work covered funnel analysis, customer segmentation, purchase-pattern analysis, insight frameworks, and reporting automation.