Aleksandr Yudin
Chief Technology Officer
15+ years exp
C++
Python
JavaScript
Kotlin
C
C#
SQL
Dart
Mobile UI/UX & Responsiveness: 5/10
Platform Native Mastery: 4/10
Active 16 days ago
+7 (900) 2306702 Invite to interview
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Overview
Technical skills
Timeline
Roles
Overview
A cross-platform Flutter developer at a solid middle level who produces well-structured app features, tests, and responsive UI. The strongest proven skill is client-side app architecture and state management with BLoC plus visual testing - evidenced by lib/src/presentation/notes_list/bloc/notes_list_bloc.dart, lib/src/presentation/notes_list/view/notes_list_screen.dart and test/widget_test.dart golden tests. There is little or no public evidence of advanced platform lifecycle/work-manager integration, offline sync conflict resolution, release automation or measured performance work.
Technical skills
C++
Python
JavaScript
Kotlin
C
C#• Senior • 15y+
SQL• Junior • 10y+
Dart• Middle
C++
OpenGL
Kotlin
Kotlin Coroutines
C#
Entity Framework Core
.NET
Dart
Dio• 6y+
Bloc• 5y+
Get_it• 5y+
Go_router• 5y+
Riverpod• 5y+
Auto_route• 4y+
MobX• 4y+
Isar• 3y+
Databases
Amazon DocumentDB
DynamoDB
MS SQL
pgvector
Qdrant
MongoDB
SQLite• 10y+
PostgreSQL• 5y+
AI/ML
AI Agents
LLM
Transformers
AI/ML
Claude
RAG• 3y+
Mobile
DataStore
MVC
Jetpack Compose
Dependency Injection
Material Design
Repository Pattern
Declarative UI
MVVM• 8y+
Realm• 8y+
Xamarin• 8y+
Flutter• 5y+
Clean Architecture• 4y+
Firebase• 3y+
DevOps
AWS
Azure
GCP
Git
eBPF
DevOps
Rest API
AWS Lambda• 5y+
CI/CD• 3y+
Game Dev
Unity
Frontend
JQuery• 15y+
Timeline
Chief Technology Officer (CTO)
•
Executive
FlowLink
•
Full-Time
Led technology and product strategy with a focus on business growth and client relationships. Defined long-term partnerships with key customers and made decisions affecting product and operational direction. Monitored and forecasted financial and product performance metrics, including pricing and competitive positioning. Produced and refined business plans and assessed marketing strategy effectiveness.
Chief Technology Officer (CTO)
•
Executive
Mamayev Konstantin Olegovich
•
Full-Time
Introduced new technologies and innovation initiatives within the company’s business direction. Evaluated project technical feasibility and selected appropriate technology approaches. Wrote and delivered production code to support the company’s software initiatives.
Lead Flutter Developer
•
Lead
Ivanov Resheniya
•
Full-Time
Concurrently developed multiple Flutter applications, handling architecture and feature implementation. Worked with state management and dependency injection to structure app logic and navigation flows. Implemented key mobile capabilities including push notifications and secure storage, and used CI/CD practices for delivery.
Bloc
Get_it
Riverpod
CI/CD
Lead Flutter Developer
•
Lead
Renda
•
Full-Time
Built and shipped multiple Flutter apps in parallel, with an emphasis on clean architecture and maintainable state management. Integrated Firebase services, including push notifications, and set up delivery automation using CI/CD. Developed app navigation and data flows using the chosen routing, DI, and HTTP layers.
Bloc
Get_it
Riverpod
CI/CDsince 2023
Firebase
Lead Flutter Developer
•
Lead
Arm-V
•
Full-Time
Prepared specifications together with the Product Owner and participated in brainstorming for non-trivial solutions. Coordinated and agreed requirements, then designed and implemented the application architecture and engineering tasks. Delivered features using Flutter 3 with clean architecture patterns, dependency injection, routing, networking, and device communication components.
Go_router
Get_it
Riverpod
Flutter
Clean Architecture
Flutter Developer
•
Middle
Code9
•
Full-Time
Translated product requirements into actionable tasks and contributed to technical planning with the project manager. Designed application architecture and implemented requested technical solutions for the mobile product. Used Riverpod for state management, Isar for local data, Firebase Messaging for notifications, and go_router for navigation.
Riverpod
Isar
Firebasesince 2023
Go_router
Flutter
Flutter Developer
•
Middle
Freelance
•
Full-Time
Developed Flutter-based solutions using a structured architecture approach and robust state management. Implemented navigation and routing, integrating AutoRoute patterns and GetIt-based dependency injection. Built and persisted local app data with SQLite, while applying clean architecture to keep modules maintainable.
Go_router
Auto_route
Get_it
Riverpod
SQLite
Clean Architecturesince 2022
Flutter
MobX
Flutter Developer
•
Middle
EPAM Systems
•
Full-Time
Designed and implemented Flutter features and managed development tasks using Bloc-based patterns and reactive programming utilities. Integrated push notification functionality and backend services backed by AWS Lambda and SNS. Worked with PostgreSQL, and implemented client networking and routing using GetIt, Dio, and GoRouter.
Blocsince 2021
AWS Lambda
PostgreSQL
Get_itsince 2021
Riverpodsince 2021
Go_routersince 2021
Fluttersince 2021
Lead Xamarin Developer
•
Lead
Keeling's Knowledge
•
Full-Time
Developed and supported a Xamarin.Forms mobile product for operational delivery tracking. Built reactive UI flows and implemented application logic using Reactive Extensions and ReactiveUI patterns. Used Realm as a local NoSQL data store and applied async task patterns during development.
Xamarin
Realm
Lead Xamarin Developer
•
Lead
8sense GmbH
•
Full-Time
Developed Xamarin.Forms applications with a focus on architecture, optimization, and maintainable task execution. Implemented mobile features using Realm for local NoSQL storage and applied MVVM patterns via Prism. Used reactive programming practices and framework-level IoC to structure dependencies and improve code quality.
Xamarinsince 2018
Realmsince 2018
MVVM
Middle Mobile Developer
Confidence: Medium Cross-platform
A cross-platform Flutter developer at a solid middle level who produces well-structured app features, tests, and responsive UI. The strongest proven skill is client-side app architecture and state management with BLoC plus visual testing - evidenced by lib/src/presentation/notes_list/bloc/notes_list_bloc.dart, lib/src/presentation/notes_list/view/notes_list_screen.dart and test/widget_test.dart golden tests. There is little or no public evidence of advanced platform lifecycle/work-manager integration, offline sync conflict resolution, release automation or measured performance work.
Platform Native Mastery
4/10
Knowing the mobile platform
Shows correct lifecycle handling for Flutter widgets and BLoC subscriptions - controller disposal, Bloc close/cancel and guarded async UI interactions - but lacks platform-specific lifecycle handling (process-death restoration, BG tasks).
Evidence
lib/src/presentation/note_edit/view/note_edit_screen.dart: initState / dispose (TextEditingController listeners, dispose) and _onWillPop dialog handling
lib/src/presentation/notes_list/bloc/notes_list_bloc.dart: _subscribeToNotes (manages StreamSubscription) and override close() that cancels subscription
lib/src/presentation/notes_list/view/notes_list_screen.dart: two-pane layout logic (LayoutBuilder, MediaQuery) and search debounce lifecycle via Timer
Mobile UI/UX & Responsiveness
5/10
Smooth mobile experience
Responsive, Material-first UI with a two-pane master-detail layout, adaptive FAB and custom animations; has golden/widget tests proving visual verification. Accessibility, RTL/dynamic type and foldable-specific adjustments are not evidenced.
Evidence
lib/src/presentation/notes_list/view/notes_list_screen.dart: LayoutBuilder two-pane logic, adaptive FAB visibility, AnimatedSwitcher for theme icon and flutter_animate usage for FAB
lib/src/presentation/note_edit/view/note_edit_screen.dart: Material TextFormField layout, cursor-preserving controller updates and PopScope integration for discard confirmation
test/widget_test.dart: multiple testGoldens and screenMatchesGolden assertions for notes_list_screen_empty and notes_list_screen_loaded
Performance & Battery
3/10
Speed and battery use
Some concrete performance-aware work (search debounce, subscription cancellation) and local DB usage, but no measured profiling, cold-start, memory or battery optimizations are present.
Evidence
lib/src/presentation/notes_list/view/notes_list_screen.dart: _onSearchChanged implements a 500ms debounce with Timer
lib/src/presentation/notes_list/bloc/notes_list_bloc.dart: _notesSubscription?.cancel() in _subscribeToNotes and close() to avoid leaks
pubspec.yaml: dependency on isar / isar_flutter_libs indicating local DB usage
Offline & Data Sync
2/10
Working offline and syncing
Uses a local DB (Isar) and provides reactive watchAllNotes stream handling, but there is no evidence of migration history, conflict resolution, background sync or offline-first conflict strategies.
Evidence
lib/src/domain/repositories/note_repository.dart: repository interface referenced by BLoC
lib/src/presentation/notes_list/bloc/notes_list_bloc.dart: _subscribeToNotes calls _noteRepository.watchAllNotes(...)
pubspec.yaml: isar and isar_flutter_libs are declared as dependencies
Device Integration
2/10
Using device features
Basic platform integration artifacts exist (iOS/Android macOS entrypoints and plugin registrant), but there is no evidence of complex device integrations or full permission flows with denial handling.
Evidence
android/app/src/main/kotlin/com/example/notes_app/MainActivity.kt: FlutterActivity integration
ios/Runner/AppDelegate.swift: imports Flutter and UIKit (iOS app entrypoint)
macos/Flutter/GeneratedPluginRegistrant.swift: registers isar_flutter_libs, path_provider_foundation, shared_preferences_foundation
Release & App Lifecycle
2/10
Building and publishing apps
Project includes platform Podfiles and pubspec launch/splash configuration and automated icon/splash tools, but no CI, release pipelines, signing automation or release management artifacts are present.
Evidence
ios/Podfile and macos/Podfile: platform and flutter pod setup
pubspec.yaml: flutter_launcher_icons and flutter_native_splash configuration
Expertise
Flutter• Middle
Mobile QA & Automated Testing• Middle
Mobile UI/UX• Middle
Technologies
JavaScript
Kotlin
C#• Senior • 15y+
Dart• Middle
.NET
Jetpack Compose
MVVM• 8y+
Realm• 8y+
Flutter• 5y+
Kotlin Coroutines
Firebase• 3y+
Entity Framework Core
Xamarin• 8y+
Clean Architecture• 4y+
Riverpod• 5y+
Bloc• 5y+
Dio• 6y+
Get_it• 5y+
Auto_route• 4y+
Go_router• 5y+
Isar• 3y+
MobX• 4y+
MVC
Repository Pattern
Dependency Injection
Declarative UI
DataStore
Material Design
Recommendations
- Deliver feature work and UI for cross-platform consumer apps - build note-editing flows, two-pane layouts and BLoC-driven screens.
- Expand on offline-first capabilities - implement a sync engine with queued idempotent operations and conflict resolution using the existing Isar-backed repository.
- Own widget- and golden-test coverage for UI changes and add basic CI to run those tests (e.g., GitHub Actions or Codemagic).
- Add measured performance work - collect simple startup/jank/memory metrics and document before/after results when optimizing expensive screens.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Junior Backend Developer
Confidence: Medium API Engineer
A backend API-focused developer at a junior level who builds small, practical integration tools. The strongest proven skill is implementing a minimal Node.js MCP/Weaviate HTTP client (braincreator/mcp-weaviate-client/index.js) that reads JSON-RPC from stdin and proxies requests to a configured MCP endpoint. There is little evidence of schema design, scalable architecture, automated tests, CI/CD, or production-grade resilience patterns in the public human-authored code.
API Design
2/10
How well APIs are designed
Basic HTTP API client logic is present (POST, headers, JSON body) and a minimal JSON-RPC error response is emitted, but there is no API versioning, idempotency, pagination, or documented error contract beyond simple JSON-RPC error objects.
Data Layer & Database
Working with databases
Not evidenced in public code
Scalability & Performance
1/10
Handling load and speed
No caching, retries, backoff, timeouts, or connection pooling are implemented; the client issues single synchronous requests per stdin line which limits scalability and resilience under load.
System Architecture
2/10
Overall system structure
Simple single-file CLI structure with environment-configured endpoint is appropriate for a small tool, but there is no evidence of modular service decomposition, config/secrets management beyond env vars, or inter-service contracts.
Security & Auth
3/10
Protecting data and access
Basic auth awareness exists via reading an API key from an environment variable and sending it in an Authorization header; however, there is no secret management, rotation, input validation, or explicit protections against malformed input.
Reliability & Observability
3/10
Stability and monitoring
Reasonable process-level reliability handling is present (SIGINT/SIGTERM handlers and an uncaughtException handler that emits a JSON-RPC error), but there is no structured logging, metrics, retries, timeouts, or correlation ids for observability.
Expertise
Backend AI & LLM• Junior
Databases & Vector Storage• Junior
Industries
Artificial Intelligence• Junior
Technologies
Rest API
Systems• mentioned only
Weaviate• mentioned only
Recommendations
- Develop small API integration components and CLI utilities that translate JSON-RPC or HTTP messages to backend services, using the existing index.js pattern as a base.
- Harden this kind of client by adding timeouts, retries with exponential backoff and jitter, input validation, and structured logging with correlation ids.
- Expand into building API gateway adapters or lightweight connectors for vector databases (Weaviate) and document the error contracts and versioning strategy.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Intern AI/ML Engineer
Confidence: Low Generalist
A developer focused on AI agent governance and security tooling, assessed at an intern-level due to no public human-authored implementation evidence. The strongest proven capability is domain knowledge in AI agent security and governance, supported by project descriptions and repository topics that reference MCP gateways, eBPF and ai-security. There is no demonstrable engineering evidence of custom model work, data pipelines, tests, deployments or original Rust/eBPF implementation files to evaluate engineering depth.
Model Architecture & Training
How well models are designed and trained
Not evidenced in public code
Data Pipeline & Feature Engineering
How data is prepared for models
Not evidenced in public code
Experimentation & Evaluation
How results are measured and tested
Not evidenced in public code
MLOps & Deployment
How models are shipped to production
Not evidenced in public code
Computational Efficiency
How efficiently computing resources are used
Not evidenced in public code
Research Depth & Innovation
Depth of research and new ideas
Not evidenced in public code
Verified artifacts
Expertise
AI Agents & Agentic Workflows• Intern
Industries
Artificial Intelligence• Junior
Cybersecurity• Intern
Technologies
AI/ML
DevOps
Python
SQL• Junior • 10y+
C++
MongoDB
PostgreSQL• 5y+
Claude
GCP
pgvector
DynamoDB
Qdrant
AI Agents
Azure
MS SQL
CI/CD• 3y+
Transformers
Git
SQLite• 10y+
AWS
LLM
RAG• 3y+
OpenGL
Amazon DocumentDB
AWS Lambda• 5y+
eBPF
Cursor• mentioned only
Systems• mentioned only
Recommendations
- Contribute implementation files that showcase core engineering - e.g., a small human-authored Rust service or eBPF sandbox demo that enforces a simple policy and includes tests.
- Build and publish a minimal end-to-end example: policy definition, enforcement hook, and audit trail with unit and integration tests to prove architecture choices.
- Focus on producing reproducible ML or security artifacts - documented benchmarks, threat-model notes, and CI that prove the governance system operates under expected constraints.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories: