🔎Senior Python Developer🔎

🟦 Join us in Luxoft!

(opportunity for PL based candidates )

💰 Paid Referrals

💻Equipment

🩺Private Medical & Dental care & Life Insurance (covered by us on Employment contract )

🏋🏽 MyBenefit program (sports card, well-being program etc.) (covered by us on Employment contract )

🌎 Internal Mobility program - possibility of rotation between projects, locations, accounts

🎓 LuxTalent platform (webinars, training, courses)

… and many more!

🟦 Project Description:

You will join a long-term, enterprise-scale project for a global client in the investment banking domain. The project focuses on building and evolving a set of mission-critical backend services that support complex business workflows, regulatory processes, and system integrations across the bank's ecosystem.

The platform is based on a distributed microservices architecture, leveraging Spring Boot, event-driven communication, and BPM-driven process orchestration. The system operates in a cloud-enabled, containerized environment, with a strong emphasis on security, scalability, resiliency, and maintainability.

You will work closely with architects, QA engineers, DevOps, and business stakeholders in an agile setup, contributing not only code but also technical direction, best practices, and mentoring.

🟦 Responsibilities:

The Python Engineer's role is to design and implement scalable, production-grade backend systems and microservices. The person we are looking for should be able to develop clean, maintainable codebases, build and scale distributed services, implement well-known communication and integration patterns, and apply best practices for large-scale distributed systems.

🟦 Mandatory Skills Description:

• At least 8+ years of practical experience in Python development and delivering production systems.

• Advanced Python proficiency, especially in scalable, clean code architecture and microservices (e.g., FastAPI, AsyncIO)

• Solid understanding of API integration patterns and inter-service communication (e.g., REST, Kafka)

• At least two backend/data-intensive solutions successfully delivered to production, ideally involving high-throughput APIs, data pipelines, or search/retrieval systems

• Practical knowledge and hands-on experience with: Relational and NoSQL databases (e.g., PostgreSQL, MongoDB), caching layers (e.g., Redis), message queues, and containerization (Docker, Kubernetes)

• Strong grasp of software engineering fundamentals: data structures, algorithms, concurrency, asynchronous programming, and API design (REST/gRPC)

• Solid understanding of testing practices: unit, integration, and end-to-end testing (e.g., pytest), plus CI/CD pipelines

• Ability to evaluate trade-offs and select appropriate tools, frameworks, and architectural patterns for a given problem

• Experience with PoC development and iterating quickly based on results

Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and infrastructure-as-code

• Strong debugging, profiling, and optimization skills for high-performance Python applications

🟦 Nice-to-Have Skills:

• Familiarity with agentic frameworks such as LangChain/LangGraph, LlamaIndex, or similar

• Practical experience integrating LLMs (e.g., OpenAI, Anthropic) into production applications, including prompt engineering and tool/function calling

• Knowledge of RAG architectures, embeddings (e.g., OpenAI), and vector databases (e.g., FAISS, Azure AI Search)

• Awareness of LLM evaluation, guardrails, and cost/latency trade-offs when designing AI-powered services

🟦 Languages:

English Upper Intermediate