PRODUCT MANAGEMENT · CONTENT CREATION · AI-FORWARD BUILDING
Tatyana Amugo
Product & AI Builder — I ship things that solve real problems and measure whether they worked.
I'm targeting product management, strategy, and AI-forward roles where I can work on hard problems, ship fast, and keep learning.
I identify problems, build solutions, and measure whether they worked. My background spans AI engineering, product delivery, and data analysis — I use all three to ship things that actually move the needle. My work spans prompt engineering, retrieval pipelines, backend APIs, and enterprise-grade deployment.
I enjoy converting ambiguous product and policy constraints into deployable systems that teams can trust.
Engineered prompt templates using Jinja for production LLM workflows integrated into the SAMS enterprise case review system, designing structured outputs and validating model responses for accuracy and reliability.
Built secure RESTful APIs and backend orchestration layers enabling AI-assisted decision workflows; reduced manual processing overhead by approximately 79% through agentic automation in a regulated government environment.
Deployed and debugged LLM integrations via Azure DevOps CI/CD; collaborated with stakeholders to define success metrics and iterate on prompt and retrieval pipeline design.
Analyzed customer behavior and market segmentation data using Python and Tableau, translating ambiguous business questions into structured, metric-driven insights that improved targeted marketing effectiveness by 15%.
Built dynamic dashboards and presented findings to cross-functional stakeholders, distilling complex data into clear recommendations for decision-makers.
Designed and deployed customer surveys with optimized question logic, improving data collection efficiency by 20% and downstream analysis quality.
Implemented and configured ERPNext modules, integrating backend services and automating workflows across departments.
Built automation pipelines that reduced manual processing by approximately 30%, improving reporting accuracy and operational efficiency.
A small prototype I built based on a Shopify shipping setup assignment prompt. The problem: many merchants abandon setup before finishing when they hit unfamiliar shipping terms. My solution: a guided assistant that asks two plain-English questions and configures the setup flow automatically. Built and deployed as an interactive prototype on Netlify.
Led a multidisciplinary team in designing an AI-powered assistive system supporting visually impaired individuals and dementia patients with spatial awareness and memory reinforcement.
Building an end-to-end LLM + RAG system that dynamically retrieves role-specific knowledge and generates structured interview simulations with feedback.
Engineered and benchmarked PaDiM, SPADE, and CLIP-based models using PyTorch and OpenCV for video anomaly detection.
Pick role + difficulty, beat the timer, stack a streak, and train like an interview game.
You join a team with a rising churn trend. How would you structure your first 7 days of analysis?
Featured reads from my Substack on practical AI concepts and real-world thinking.