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Andrew Triapitsyn

Backend Engineering • AI & Data Systems • Product Analytics • GenAI Evaluation

MSc Computer Science student specializing in Artificial Intelligence & Machine Learning.
Building production-style backend systems, analytics platforms, AI workflows, and data-driven business solutions.

LinkedInGitHub


About Me

I am an AI, backend systems, and data analytics professional with experience across GenAI evaluation, backend engineering, business intelligence, operational analytics, process improvement, and digital operations.

My recent experience includes working as a Gen AI Annotator on a Meta vendor project through Covalen, where I evaluated AI-generated and user-facing content against detailed quality, safety, and policy guidelines. This strengthened my practical understanding of:

  • human-in-the-loop AI evaluation
  • LLM output quality assessment
  • structured feedback systems
  • decision consistency
  • policy-aware review workflows
  • Trust & Safety operations
  • content quality signals
  • user intent interpretation

Alongside this, I am pursuing an MSc in Computer Science focused on Artificial Intelligence & Machine Learning while building practical engineering projects across:

  • event-driven backend systems
  • distributed architectures
  • product analytics platforms
  • business intelligence workflows
  • SQL and relational analytics
  • observability and monitoring
  • AI-assisted workflows
  • automation and process optimization

My portfolio combines backend engineering, AI systems, analytics, and operational thinking with a strong focus on practical architecture, scalability, maintainability, and business value.


Current Focus

  • Backend & Distributed Systems: Java, Spring Boot, Kafka, PostgreSQL, Docker, observability, and event-driven architectures

  • AI & GenAI Evaluation: LLM quality assessment, structured evaluation workflows, prompt engineering, and AI-assisted systems

  • Data Analytics & Business Intelligence: SQL, Python, Power BI, KPI reporting, dashboards, and data quality workflows

  • Product Analytics: funnels, retention, segmentation, behavioural insights, and metric-driven product thinking

  • Trust & Safety Analytics: content quality signals, classification consistency, policy-risk concepts, and moderation workflows

  • Repository Engineering: clean architecture, reproducible infrastructure, integration testing, and recruiter-friendly technical documentation


Core Areas

Area Focus
Backend Engineering Event-driven systems, REST APIs, Kafka workflows, observability, Docker, clean architecture
AI & GenAI Evaluation LLM output assessment, human-in-the-loop review, prompt engineering, AI-assisted workflows
Product Analytics User behaviour, funnels, retention, segmentation, KPI frameworks, product metrics
Data Analytics & BI SQL, Python, Power BI, reporting, KPI tracking, dashboards, data quality
Trust & Safety Content quality, moderation workflows, policy-risk awareness, classification consistency
Business Analysis Process mapping, workflow improvement, stakeholder communication, operational analysis
Operations & Delivery Incident handling, service operations, escalation workflows, reporting, coordination

Featured Engineering Projects

Project Description
PulseStream Event-driven backend analytics platform built with Java 21, Spring Boot, Kafka, PostgreSQL, Testcontainers, Docker, and Clean Architecture principles
SentinelFlow Business observability and monitoring engine focused on asynchronous workflows, alerting pipelines, validation systems, and operational visibility
ProductPulse AI-powered business product analytics decision engine focused on KPI intelligence, churn analysis, segmentation, and recommendation logic
SQL Relational Analysis Advanced SQL analytics repository using PostgreSQL, relational modeling, business metrics, validation pipelines, and analytical reporting

My Stack and Tools

Backend & Distributed Systems

Java 21 Spring Boot Kafka Testcontainers Micrometer Prometheus Grafana Docker

Programming & Query Languages

Python SQL Bash JavaScript TypeScript

Data Analytics & Business Intelligence

Pandas NumPy Jupyter Power BI Excel Google Analytics

Databases & Data Platforms

PostgreSQL MySQL SQL Server BigQuery

AI, Machine Learning & GenAI

scikit-learn PyTorch OpenAI Generative AI LLM Evaluation Prompt Engineering

Development, Collaboration & Workflow

Git GitHub GitHub Actions VS Code Jira


Selected Experience

Role Focus
Gen AI Annotator — Covalen (Client: Meta) GenAI evaluation, AI-generated content review, structured quality assessment, user intent analysis, policy-aware workflows
Duty Manager — Powerscourt Springs Health Farm Operations leadership, process improvement, incident handling, workflow optimization, customer operations
Duty Manager / Night Supervisor — Wilton Hotel Bray Operational continuity, reporting, escalation management, audits, onboarding, service quality
Junior Database & Python Specialist SQL, Python automation, relational databases, data validation, reporting, analytics workflows

Certificates

  • Google Advanced Data Analytics Professional Certificate
  • Google Data Analytics Professional Certificate
  • IBM Data Science Professional Certificate
  • Microsoft Power BI Data Analyst
  • Microsoft SQL Server Certification
  • Google AI Essentials
  • Google Prompting Essentials
  • AI Agent Developer
  • Generative AI Leadership & Strategy
  • Organizational Strategy with Generative AI & AI Agents
  • Google Project Management Professional Certificate
  • Oxford Saïd — Advanced Business Analytics with AI
  • Oxford Saïd — Future Ready Leadership
  • EF SET English Certificate (C1)

Portfolio Direction

I am currently building repositories focused on:

  • backend engineering and distributed systems
  • event-driven architectures
  • AI product analytics
  • observability and operational intelligence
  • business intelligence and KPI systems
  • SQL-driven analytics
  • GenAI evaluation workflows
  • Trust & Safety analytics
  • automation and workflow optimization

Career Direction

I am focused on opportunities across:

  • Backend Engineering
  • AI & Data Systems
  • Product Analytics
  • Business Intelligence
  • GenAI Evaluation
  • Trust & Safety Analytics
  • Digital Business Analysis

My long-term goal is to combine backend engineering, AI systems, analytics, and operational thinking to help organizations build scalable, reliable, and intelligent digital platforms.

Pinned Loading

  1. olist-ecommerce-analytics-pipeline olist-ecommerce-analytics-pipeline Public

    End-to-end e-commerce analytics pipeline using PostgreSQL, SQL quality tests, Python, Streamlit, and the Olist dataset.

    Jupyter Notebook

  2. sentinelflow-business-observability-engine sentinelflow-business-observability-engine Public

    Production-ready business observability engine with async checks, resilience patterns, tracing, Prometheus metrics, and alerting.

    Python

  3. PulseStream PulseStream Public

    Event-driven business analytics platform built with Java 21, Spring Boot, Kafka, PostgreSQL, and Clean Architecture principles.

    Java 1

  4. ProductPulse ProductPulse Public

    Local-first SaaS analytics decision engine for governed KPIs, churn risk, revenue leakage, and explainable recommendations.

    Python 1

  5. Algorithms-Data-Structures-Lab Algorithms-Data-Structures-Lab Public

    Final data structures and algorithms project in Python: linked lists, recursion, Dijkstra, heap visualization, DFS/BFS traversal, greedy/DP optimization, and Monte Carlo simulation.

    Python