Solution Architect – Python with GenAI

Company Overview

EPAM Systems is a premier global digital transformation service provider with roots in advanced software engineering since 1993. It leads in designing digital and physical products and engineering digital platforms, serving clients across over 45 countries with hybrid teams. EPAM is recognized for its innovation and growth, listed in the S&P 500 and Forbes Global 2000.

Job Overview

We are looking for a Solution Architect with expertise in Python and Generative AI (GenAI) to develop and implement enterprise-grade GenAI systems. Join our team to drive technical discovery, develop reusable components, and establish guidelines and best practices for large language model deployment in client solutions.

Key Responsibilities

• Architect comprehensive GenAI solutions incorporating Retrieval-Augmented Generation (RAG), Agents, and Multi-Agent Systems tailored for enterprises.
• Create and maintain reusable accelerators and reference models to streamline solution delivery.
• Lead discovery sessions and provide direct technical mentorship and guidance to development teams.
• Define frameworks for evaluating and establishing standards for LLM applications.
• Work closely with cross-functional teams to ensure designs are scalable, maintainable, and robust.
• Design microservices using appropriate design patterns and modern frameworks like FastAPI.
• Oversee integration and configuration of cloud infrastructure across AWS, Microsoft Azure, and Google Cloud Platform.
• Manage containerization strategies using Docker and orchestration with Kubernetes.
• Evaluate and select vector databases such as Pinecone, Weaviate, or Chroma for effective GenAI data management.
• Apply LLMOps principles and monitoring tools to optimize production deployments and ensure operational excellence.
• Implement prompt management and RAG evaluation techniques to improve application accuracy and performance.
• Engage in knowledge-sharing activities and mentor fellow architects within the organization.
• Maintain highest standards of production-quality Python code in all projects.
• Lead continuous improvements aiming at scalability and system design enhancements.

Required Qualifications and Skills

• 9 to 14 years of experience in software development with strong solution architecture and system design capabilities.
• Expert-level Python coding skills producing production-ready quality software.
• In-depth familiarity with microservices, design patterns, FastAPI, Redis, Elasticsearch, and Kafka.
• Hands-on experience developing advanced GenAI applications including Agents, Multi-Component Processes (MCP), RAG, Agentic RAG, and GraphRAG.
• Strong knowledge of LangGraph, LangChain, and related orchestration frameworks.
• Experience in evaluating large language models, managing RAG evaluations, and prompt engineering.
• Proven success in delivering scalable GenAI applications in production environments.
• Experience with cloud service platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Familiarity with container technologies including Docker and Kubernetes orchestration.
• Working knowledge of vector databases like Pinecone, Weaviate, or Chroma.
• Understanding and application of LLMOps methodologies and monitoring systems.
• Strong leadership aptitude to guide and coordinate engineering teams effectively.
• Excellent collaboration skills in client-facing and cross-functional team settings.
• Proficient written and spoken English communication at B2 level or above.

Desired Additional Expertise

• Experience with classical machine learning: feature engineering, model training, and evaluation processes.
• Exposure to knowledge graph development and fine-tuning of models.
• Previous consultancy or client engagement experience is a plus.