Python Backend Platform Engineer (AI Software)

About the position We are Quadcode, a fintech company excelling in financial brokerage activities and delivering advanced financial products to our global clientele. Our flagship product, an internal trading platform, is offered as a Software-as-a-Service (SaaS) solution to other brokers. We’re looking for a Python Engineer who is confident in designing and building complex, scalable systems, from core backend services to infrastructure and data flows — for building the next-gen AI IDE (RAG, multi-model, GPU workloads) in Quadcode.ai, our new startup within a stable company. At Quadcode.ai, we’re building a next-generation AI IDE platform for developing complex software systems. The platform provides a powerful, fully integrated environment where users can build code, design, images, audio, video, and complex digital products — all while AI helps analyze context, automate workflows, and accelerate production. It turns complex technical processes into smooth, intuitive experiences across desktop, mobile, and web, giving engineers full control over scalable, high-performance systems. What makes our platform strong Multi-Model AI approach — seamlessly working with multiple AI models for different scenarios. Multimodal environment — a unified workspace for code, design, images, audio, video, and documents. AI-first interface architecture — designed around AI workflows from the ground up, not retrofitted afterward. Proprietary RAG framework — handling large volumes of context and complex production-level tasks. Hybrid development approach — powerful AI automation combined with full manual control for engineers. Our product has successfully passed the MVP and internal testing stages, has recently launched on the market, and we are continuing to test and improve it. We work in the EET/EEST time zone, with a team daily meeting at 12:00 PM. Join us to build the future of development together!

Responsibilities

• Design and develop backend services using FastAPI / Flask.
• Build and maintain internal and external APIs for both product features and AI-driven scenarios.
• Work with PostgreSQL and PgBouncer: design schemas, optimize queries, and manage database load.
• Utilize Redis for caching, queues, pub/sub, and other system-level tasks.
• Develop asynchronous processes and background workers using Celery.
• Containerize services with Docker and Docker Compose.
• Manage orchestration with Docker Swarm and Kubernetes.
• Deploy and maintain AI workers in GPU cloud environments, including RunPod and Vast.ai.
• Set up CI/CD pipelines, monitoring, logging, and basic SRE practices.
• Participate in designing scalable and fault-tolerant backend systems.
• Make architectural decisions for high-load and AI-native components.
• Contribute to the backend of the AI IDE itself, including integrations with AI models and RAG subsystems.

Requirements

• Minimum 3 years of commercial experience in Python backend development, preferably focused on platform engineering.
• Deep understanding of Python internals and interpreter mechanics, memory management, and execution model.
• Familiarity with GIL and practical ways to work around its limitations: multiprocessing, asyncio, C-extensions.
• Confident working with async/await and a solid understanding of the event loop.
• Strong SQL skills: complex queries, indexes, execution plans, and optimization.
• Practical experience with PostgreSQL: performance tuning, replication, partitioning.
• Understanding of connection pooling and experience with pgbouncer.
• Experience designing scalable and highly available systems.
• Understanding of architectural patterns: CQRS, Event Sourcing, microservices.
• Experience with brokers and task queues: Celery, Redis, RabbitMQ.
• Confident using Docker, Docker Swarm, and Kubernetes.
• Understanding of DevOps practices: IaC, monitoring, alerting, deployment automation.
• Fluent Russian is a must (minimum C2).
• Technical English (minimum B1+).

Nice-to-haves

• Experience developing IDEs, LSPs, or other language tooling.
• Familiarity with RAG systems and LLM APIs.
• Hands-on experience with RunPod or Vast.ai.
• Knowledge of C/C++ or Rust for performance-critical components.
• Experience working with GPU infrastructure.

Benefits

• Full-time remote work (External Vendor contract) with flexible hours — work where and when you’re most productive.
• Competitive compensation in EUR or crypto.
• Build a technically ambitious product that has real impact on the development market.
• Directly shape the architecture, engineering decisions, and evolution of the AI platform.
• Work with cutting-edge AI tools and GPU workloads.
• Collaborate with a team of passionate, AI-focused professionals.
• Enjoy a positive, friendly, and motivating environment that encourages experimentation.

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