Anna Sbrodova
Senior Software Engineer / Principal Backend Engineer
Technically proficient and product-minded professional with 12+ years of software engineering experience across enterprise platforms, distributed backend systems, cloud-native infrastructure, and event-driven architectures within fintech, logistics, automation, and large-scale e-commerce environments. Over the past several years, specialised in designing and scaling high-throughput Go/GCP backend systems focused on distributed processing, reliability engineering, and cloud-native platform delivery.
Strong end-to-end ownership capability, able to take complex backend products from stakeholder requirements and system design through architecture, implementation, infrastructure, observability, and production. Experienced in working independently on complex technical problems and translating product and business requirements into well-structured backend architectures.
Key Career Accomplishments
- Architected and delivered a Go/GCP event-driven processing platform handling tens of thousands of Kafka events under peak load, ensuring stable throughput and fault-tolerant execution across distributed backend services.
- Designed large-scale distributed compute pipelines orchestrating hundreds of parallel Cloud Run jobs, each processing millions of BigQuery rows per execution for high-volume data transformation workloads.
- Built an enterprise cloud expenditure chargeback platform from scratch, translating complex multi-tenant cloud billing and SaaS cost models into scalable automated business logic and production-ready distributed workflows.
- Supported large-scale e-commerce infrastructure at ManoMano handling ~50M monthly visits and scaling from 3,000-5,000 concurrent users to 15,000-30,000+ users during Black Friday peak events.
- Solved critical distributed consistency challenges by implementing Transactional Outbox and Inbox patterns, eliminating dual-write vulnerabilities and ensuring resilient, idempotent event delivery across business-critical financial systems.
- Reduced BigQuery operational expenditure by ~18% through query optimisation, schema redesign, and execution-flow improvements, while also improving Cloud SQL infrastructure efficiency and deployment automation across cloud-native environments.
Technical Track Record
Hands-on Technical Lead
EPAM Systems
Mar 2025 — Present
Design and deliver distributed backend systems on Go and GCP from initial stakeholder requirements through system design, implementation, deployment, and production hardening. Lead engineering across large-scale data pipelines, asynchronous processing systems, and multi-service distributed environments spanning Kafka, Pub/Sub, BigQuery, Cloud Run, and GKE.
- Owned end-to-end architecture across cloud-native systems spanning Kafka, Pub/Sub, BigQuery, Cloud Run, and GKE, defining service boundaries and ensuring scalable system design.
- Delivered and operated a 15+ microservice GKE ecosystem structured around event-driven patterns, ensuring loose coupling, independent service scalability, and production resilience.
- Built centralised CI/CD deployment orchestration tooling using automated YAML manifests capable of calculating dependency-aware microservice deployment sequencing.
Tech: Golang, GCP, Terraform, Cloud Run, Pub/Sub, BigQuery, GKE, Kubernetes.
Senior Backend Engineer / Technical Lead
EPAM Systems
May 2023 — Mar 2025
- Built and maintained Go-based distributed microservices on GCP supporting enterprise-scale workloads across multiple high-throughput backend systems.
- Designed event-driven architectures using Kafka, Redis, and GCP services (Pub/Sub, Cloud Run), enabling scalable asynchronous processing and reliable message handling.
- Introduced structured observability practices (metrics, logs, tracing) across services, improving system visibility and reducing blind spots in distributed workflows.
Tech: Golang, GCP, Terraform, PostgreSQL, Redis, Grafana, Loki, Docker.
Senior Software Engineer
ManoMano
Feb 2022 — Apr 2023
- Supported production e-commerce systems handling 3,000-5,000 concurrent users (~50M monthly visits) across distributed Go-based backend services.
- Scaled backend infrastructure during Black Friday peak events to 15,000-30,000+ concurrent users, maintaining system stability during extreme load spikes.
- Improved performance of critical Go services by removing bottlenecks in data access layers and stabilising high-concurrency transactional workflows under production load.
Tech: Golang, GCP, Spring Boot, Kafka, Redis, MongoDB.
Early Career History
IBA, Standard Bank & IBM, WF-TESSI
2014 — 2021
- Mid to Senior roles focusing on Java Enterprise logistics, RPA automation (Workfusion), and full-stack development for Corporate Banking.
Architectural Deep Dives
Challenge: Ensuring data consistency across distributed microservices when updating a local database and publishing a domain event to a message broker (Cloud Pub/Sub) simultaneously. A failure in either step leads to system-wide inconsistencies.
Solution: Architected a Transactional Outbox pattern using Golang and Cloud SQL (PostgreSQL). Events are saved in the same transaction as the business entity. A separate CDC (Change Data Capture) or polling worker securely publishes these events to Pub/Sub with at-least-once delivery guarantees.
Impact: Achieved 100% data consistency in high-concurrency environments without relying on distributed transactions (2PC), significantly improving system resilience and throughput.
The Tooling Lab (Open Source)
Aura Tracker GCP ↗
Model Context Protocol (MCP) Server
- Built a commercial-grade foundation Go-based MCP server exposing 67+ infrastructure tools across 24 GCP domains, enabling secure AI-driven cloud orchestration.
- Designed a strict Hexagonal Architecture with rate-limited, async execution and a pluggable module system for scalable tool expansion.
- Implemented enterprise-grade safety and observability layers including dry-run/safe-apply controls and PII anonymisation for secure LLM-integrated infrastructure access.
Tech: Golang, GCP SDK, MCP Protocol, AI Tooling.
Core Technical Stack
Primary Languages & Cloud
Go (Golang), Google Cloud Platform (GCP), SQL
Cloud-Native Platforms
GKE (Google Kubernetes Engine), Cloud Run, Pub/Sub, BigQuery, Cloud SQL
Distributed Systems & Architecture
Event-Driven Architecture, Hexagonal Architecture (Ports & Adapters), Transactional Outbox Pattern, Transactional Inbox Pattern, Dual-Write Problem Resolution, High-Load System Design
Data & Messaging Systems
Kafka, Redis, PostgreSQL, MongoDB, IBM MQ
Infrastructure & DevOps
Terraform, Kubernetes, Docker, CI/CD automation, Eventarc
Observability & Reliability Engineering
Prometheus, Grafana, Loki, OpenTelemetry, GCP Monitoring, Structured Logging, Proactive Alerting Systems
Platform Engineering & Internal Tooling
CI/CD pipeline automation, dependency-aware deployment orchestration, microservice release automation, GitOps-style workflows
AI / MCP / Advanced Systems
Model Context Protocol (MCP), cloud orchestration tooling, AI-safe infrastructure APIs, secure LLM tool exposure patterns
Contractor Availability
Contract Readiness: Fully equipped for international remote engagement; self-managed taxation in Indonesia (WITA / UTC+8 timezone).