Solution Architect – Python with Generative AI

About the Role and Company

EPAM Systems, established in 1993, is a leading global provider of digital transformation and software engineering services. Renowned for its industry leadership and innovative approach, EPAM serves clients worldwide across various continents, driving enterprise, education, and health platforms that enhance user experiences. Recognized by several indexes such as the S&P 500 and Fortune's lists, EPAM offers the opportunity to join a top-tier technology organization.

Key Responsibilities

• Architect and design comprehensive Generative AI solutions including Retrieval Augmented Generation (RAG) models, Agents, and Multi-Agent frameworks tailored for extensive enterprise deployment.
• Create reusable accelerator modules and reference designs to standardize and streamline solution delivery.
• Lead technical exploration meetings and provide actionable assistance to engineering teams during project development.
• Develop evaluation mechanisms and establish developmental standards guiding the construction of LLM-driven applications.
• Work collaboratively across teams to ensure architectural solutions are scalable and maintainable for the long term.
• Develop microservices architecture by leveraging proven design patterns and contemporary frameworks.
• Oversee the integration of cloud infrastructure components spanning AWS, Microsoft Azure, and Google Cloud Platform (GCP).
• Manage containerized deployments and orchestration using Docker and Kubernetes technologies.
• Assess and select appropriate vector database technologies such as Pinecone, Weaviate, or Chroma to support GenAI implementations.
• Implement LLM Operations (LLMOps) methodologies and monitoring capabilities to enhance the reliability and quality of production systems.
• Contribute to prompt engineering and evaluation of Retrieval Augmented Generation to boost system effectiveness.
• Engage in mentoring activities and share expertise widely within the architecture community.
• Maintain stringent coding practices to ensure Python code quality meets production standards.
• Continuously drive improvements in system architecture and scalability of solutions.

Essential Qualifications

• Between 9 to 14 years of experience in software development with strong expertise in solution architecture and systems design.
• Advanced proficiency in Python development with an emphasis on production-quality code.
• Experience with microservices design including architectural frameworks like FastAPI, and technologies including Redis, Elasticsearch, and Kafka.
• Practical exposure to generative AI development involving Agents, Multi-Context Processing (MCP), and various RAG frameworks such as Agentic RAG and GraphRAG.
• Proficient in orchestration platforms such as LangGraph and LangChain.
• Hands-on in assessing LLMs and RAG systems alongside prompt management and optimization.
• Track record of delivering scalable GenAI applications suitable for live production environments.
• Experienced with major cloud platforms (AWS, Azure, GCP) and cloud resource integration.
• Skilled in containerization and orchestration tools, specifically Docker and Kubernetes.
• Knowledgeable about vector databases including Pinecone, Weaviate, and Chroma.
• Understanding of LLMOps principles and supportive monitoring tools.
• Proven leadership abilities to guide engineering teams effectively.
• Comfortable working in client-facing roles while promoting collaborative teamwork.
• English communication skills at a B2 level or higher, both verbal and written.

Additional Desirable Skills

• Experience with traditional machine learning tasks such as feature engineering, model training, and evaluation.
• Familiarity with knowledge graph construction and fine-tuning techniques.
• Previous consulting experience or engagement in roles with direct client interaction.