Senior Python Engineer

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.

• At least 5+ years of practical experience in Python development and delivering production systems
• Proficiency in advanced Python, especially in scalable, clean code architecture and microservices (e.g., FastAPI, asyncio)
• Understanding of API integration patterns and inter-service communication (e.g., REST, Kafka)
• Track record of 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), and message queues
• Experience with containerization (Docker, Kubernetes)
• Strong grasp of software engineering fundamentals: data structures, algorithms, and concurrency
• Skills in asynchronous programming and API design (REST/gRPC)
• Understanding of testing practices: unit, integration, and end-to-end testing (e.g., pytest), plus CI/CD pipelines
• Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and infrastructure-as-code
• Strong debugging, profiling, and optimization skills for high-performance Python applications
• English proficiency at B2 level or higher

Nice to have:

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

• Develop and maintain Python applications that meet business requirements and technical specifications
• Collaborate with cross-functional teams to design, develop, and implement software solutions
• Utilize Azure services and technologies to build scalable and efficient applications
• Implement event-based design patterns to enhance application functionality and performance
• Apply knowledge of RAG architecture to relevant projects
• Troubleshoot, debug, and optimize code to ensure high performance and reliability
• Stay updated with the latest industry trends, technologies, and best practices in Python development and cloud computing
• Evaluate trade-offs and select appropriate tools, frameworks, and architectural patterns for a given problem
• Develop PoCs and iterate quickly based on results