Vetted Vertex AI Professionals

“At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.”

“AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.”

“AI engineer building and deploying deep-learning-based optimization/control systems for petrochemical plants, with a focus on maintaining operational stability under real-world constraints. Core contributor to model and inference design; introduced a stability-focused non-linear objective and sped up second-layer optimization via on-the-fly first-order approximations. Experienced using Kubernetes for end-to-end testing and effective in translating customer expectations into measurable evaluation plots for non-technical stakeholders.”

“FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.”

“Engineering leader from Blackline who has repeatedly rescued and delivered high-visibility products by resetting roadmaps, tightening execution (better specs/estimation), and accelerating team velocity. Scaled a distributed org from ~20 to ~40 engineers by building a new India team with strong hiring rubrics and governance-as-code/SDLC consistency. Also modernized legacy systems into microservices (Kafka/Kubernetes/Apigee) and drove hackathon-to-production innovation using Google Vertex AI.”