Khushdil Ikhtiyori
Python Developer
SeniorBackend Developer
5years in DevOps
7/10API Design
4years with Python
Overview
Backend API engineer (senior-level, ~4.0) focused on building robust REST services for a food-ordering platform and its partner integration. The strongest proven skill is designing reliable HTTP APIs with idempotency and transactional persistence, evidenced by services/kitchen-api/src/avito_kitchen/presentation/http/orders.py and infrastructure/repositories/orders.py. The public code shows solid testing, migrations and observability but does not demonstrate advanced distributed systems techniques like brokered queues, circuit breakers or measured performance optimizations.
Phone
Timeline
Moscow State University (MSU)
Bachelor's Degree ·
Прикладная математика и информатика
Backend Developer (Python)
·
Middle
FirstByte
·
Full-Time
Developed the backend for an online pharmacy, implementing an order processing service. Built товар reservation with transactional logic and row-level locking to prevent overselling under concurrent requests. Implemented caching for product catalog and cards with invalidation, added retry handling with exponential backoff and a dead-letter queue after failures, and improved service performance for reservation flows. Integrated an external payment provider by migrating from a blocking SDK to native async HTTP using httpx, and implemented a two-step user registration with TTL-based storage and asynchronous confirmation code delivery via Celery, including integration testing with CI-backed PostgreSQL.
Python
PostgreSQL
HTTPX
Celery
Technical skills
Python
Python
FastAPI
HTTPX
Asyncio
Uvicorn
Pydantic
Requests
DevOps
GitHub
Rest API
Docker Compose
Containers
Alpine Linux
CI/CD
Databases
PostgreSQL
QA
Pytest
AI/ML
Machine Learning
Senior Backend Developer
Confidence: High API Engineer
Backend API engineer (senior-level, ~4.0) focused on building robust REST services for a food-ordering platform and its partner integration. The strongest proven skill is designing reliable HTTP APIs with idempotency and transactional persistence, evidenced by services/kitchen-api/src/avito_kitchen/presentation/http/orders.py and infrastructure/repositories/orders.py. The public code shows solid testing, migrations and observability but does not demonstrate advanced distributed systems techniques like brokered queues, circuit breakers or measured performance optimizations.
API Design
7/10
How well APIs are designed
Well-structured HTTP API with versioned routes, explicit idempotency header handling, Pydantic request models and a consistent error envelope documented and tested.
Evidence
services/kitchen-api/src/avito_kitchen/presentation/http/orders.py: Idempotency-Key header validation and handling in create_order
services/kitchen-api/src/avito_kitchen/presentation/http/partner_orders.py: HTTPBearer-based partner authentication and partner endpoints under /api/v1/partner
services/kitchen-api/src/avito_kitchen/observability.py and tests/test_openapi.py: centralized ErrorResponse/contract and OpenAPI export checks
Data Layer & Database
7/10
Working with databases
Raw SQL with explicit transaction boundaries, use of connection pooling, careful locking and idempotency key persistence plus migration runner present.
Evidence
services/kitchen-api/src/avito_kitchen/infrastructure/repositories/orders.py: transaction around idempotency key insert, FOR SHARE queries and order + items insert using executemany
services/kitchen-api/src/avito_kitchen/infrastructure/database.py: Database pool wrapper using asyncpg
services/kitchen-api/src/avito_kitchen/infrastructure/migrations.py: migration runner that applies versioned SQL files
Scalability & Performance
4/10
Handling load and speed
Basic scalability primitives present (async IO, connection pooling); no advanced queuing, caching invalidation, or measured performance tuning shown.
Evidence
pyproject.toml: dependencies include asyncpg and uvicorn indicating async stack
services/kitchen-api/src/avito_kitchen/infrastructure/database.py: asyncpg pool usage and acquire patterns
tests/e2e/test_order_flow.py: end-to-end HTTP-based integration between services (no message broker)
System Architecture
5/10
Overall system structure
Clear service boundaries and reproducible architecture (two services, PlantUML docs, separate packages and lifecycles); decomposition is pragmatic rather than distributed-systems complex.
Evidence
pyproject.toml: separate packages under services/kitchen-api and services/restaurant-api
docs/README.md and docs/c4.puml referenced by tests/test_documentation.py: architecture diagrams and verified boundaries
services/kitchen-api/src/avito_kitchen/main.py: lifespan and app composition wiring database and observability
Security & Auth
6/10
Protecting data and access
Security-aware at the API boundary with bearer auth for partner endpoints, parameterized SQL queries, Pydantic validation and secrets typed in settings; no advanced token lifecycle or RBAC was implemented.
Evidence
services/kitchen-api/src/avito_kitchen/presentation/http/partner_orders.py: HTTPBearer usage to protect partner API
services/kitchen-api/src/avito_kitchen/presentation/http/orders.py: Pydantic models with validators for input validation
services/kitchen-api/src/avito_kitchen/infrastructure/repositories/orders.py: parameterized asyncpg queries preventing SQL injection
Reliability & Observability
6/10
Stability and monitoring
Good observability practices with structured error envelope, request id propagation and tests asserting error contracts and request id handling; limited evidence of retries/backoff or circuit breakers.
Evidence
services/kitchen-api/src/avito_kitchen/observability.py: JsonFormatter, request_context and exception handlers
services/restaurant-api/src/restaurant_api/observability.py: mirrored observability implementation for the partner service
tests/test_observability.py: tests asserting request id propagation and error envelope
Expertise
Python· Middle
Microservices & API Architecture· Middle
Industries
Food & Beverages· Middle
Technologies
Rest API· since 2021 · 5+ projects
FastAPI· since 2022 · 4 projects
Uvicorn· since 2022 · 4 projects
Recommendations
- Develop/maintain RESTful ordering and partner-integration APIs with strong idempotency and transactional guarantees.
- Implement production hardening work: observability dashboards, request-level metrics and well-reasoned retry/backoff policies for upstream HTTP calls.
- Own SQL schema evolution and migration strategy including documented migration history and review for indexing and query plans.
- Integrate a lightweight queue or change-data-capture for decoupling partner flows when throughput/growth requires it.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Senior DevOps Engineer
Confidence: High Generalist
Backend engineer focused on building small service platforms and API integrations at a senior (lower) level with strong emphasis on correctness and testability. The strongest proven skill is building reliable transactional APIs with idempotency and end-to-end tests as shown by the Postgres-backed Orders repository (services/kitchen-api/src/avito_kitchen/infrastructure/repositories/orders.py) and the e2e test suite (tests/e2e/test_order_flow.py). There is limited public evidence of production-grade CI/CD pipelines, cloud cost/scale design or formal runbooks and incident playbooks.
CI/CD Pipelines
2/10
Automated build and deploy
Minimal CI/CD hygiene is present (Makefile targets and local commands) but there are no reusable workflows, gating, artifact signing or pipeline engineering artifacts.
Infrastructure as Code
1/10
Managing servers with code
No true Infrastructure-as-Code (Terraform/CloudFormation/CDK) or remote state/lock evidence; database migrations exist but full IaC practices are not shown.
Containerization & Orchestration
4/10
Working with containers
Containerization is solid for a demo: multi-service Dockerfiles, non-root user creation and Compose with healthchecks and service ordering are implemented, but no cluster orchestration, resource tuning or advanced Pod-level resilience settings are present.
Observability & Monitoring
4/10
Watching system health
Structured observability is implemented at the application level (JSON formatting, request id propagation and HTTP error envelope) and covered by tests, but there is no evidence of SLI/SLO, alert routing or burn-rate rules.
Reliability & Incident Response
4/10
Keeping systems up
Reliability-focused design is visible: idempotency keys, transactional order creation, readiness/health endpoints, separate migrate step and end-to-end tests demonstrate incident-aware practices, but there is no documented runbook, canary strategy or chaos rehearsal artifacts.
Cloud & Cost Optimization
1/10
Smart use of the cloud
No cloud cost or autoscaling practices are present; only basic container images and environment variable defaults are used which is useful for local demos but not evidence of cloud cost engineering or IAM/workload identity.
Expertise
Observability & Monitoring· Middle
Site Reliability Engineering· Middle
Industries
Commerce· Middle
Technologies
CI/CD
Containers
Docker Compose
Pydantic
Alpine Linux
Recommendations
- Develop transactional backend APIs and integration points that require idempotency, strong DB transactions and end-to-end tests (work on checkout/order flows and partner integrations).
- Implement observable platform components: extend structured logging to tracing and add SLI/SLOs and alerting playbooks tied to incidents (build on existing observability.py and tests).
- Own CI/CD pipelines and release gates: add reusable workflows, deploy gates, canary or progressive delivery steps and pipeline tests to move demo Compose flows into gated CI for production.
- Expand infra-as-code and cloud practices: add Terraform/CloudFormation with remote state and automated migrations, and introduce autoscaling and IAM workload identity patterns for cloud deployments.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Intern QA Engineer
Confidence: Low Generalist
Junior Python developer focused on testing tooling and asynchronous HTTP clients. The strongest proven skill is pytest and test tooling, supported by concrete artifacts such as the _pytest package modules and example test suites. There is little to no original public evidence of owning end-to-end automation frameworks, negative-path or contract testing, CI test integration, or performance/load testing work.
Test Automation Frameworks
Building automated tests
Not evidenced in public code
Test Coverage & Strategy
What and how to test
Not evidenced in public code
API & Integration Testing
Testing how parts work together
Not evidenced in public code
Performance & Load Testing
Testing speed under load
Not evidenced in public code
Bug Reporting & Analysis
Finding and describing bugs
Not evidenced in public code
CI Test Integration
Running tests automatically
Not evidenced in public code
Technologies
Python· since 2022 · Senior · 4 projects
Asyncio· since 2022 · 4 projects
Pytest
HTTPX· since 2022 · 4 projects
Requests
Recommendations
- Develop unit and integration tests and pytest plugins for Python services using pytest and its plugin APIs.
- Implement async HTTP client code and integration tests using asyncio with HTTPX and Requests for service-to-service interactions.
- Build test utilities and example test suites (fixtures, factories, and isolated conftest setups) to improve test reproducibility and onboarding.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Job preferences
- Work permits
- Russia
- Employment type
- Full-Time
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