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Solution Architect – Python with GenAI
EPAM Systems, Inc.
Remote · India Full-time Senior Today
About the role
About
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi‑national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting‑edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are seeking a Solution Architect specializing in Python and GenAI to design and build production‑grade GenAI solutions for enterprise clients.
Join our Solution Architecture team to lead technical discovery, develop reusable accelerators, and define best practices for LLM applications. Apply now to contribute to cutting‑edge GenAI projects and help clients achieve transformative results.
Responsibilities
- Design end‑to‑end GenAI architectures including RAG, Agents, and Multi‑Agent Systems for enterprise clients
- Build reusable solution accelerators and reference implementations to standardize delivery
- Lead technical discovery sessions and provide hands‑on guidance to engineering teams
- Define evaluation frameworks and establish best practices for large language model (LLM) applications
- Collaborate with cross‑functional teams to ensure scalable and maintainable system designs
- Implement microservices architectures using design patterns and modern frameworks
- Oversee integration of cloud infrastructure components such as AWS, Azure, or GCP
- Manage containerization and orchestration using Docker and Kubernetes
- Evaluate and select vector databases like Pinecone, Weaviate, or Chroma for GenAI solutions
- Apply LLMOps practices and monitoring to optimize production deployments
- Support prompt management and RAG evaluation to enhance application accuracy
- Contribute to knowledge sharing and mentoring within the architecture group
- Ensure production‑grade code quality in Python applications
- Drive continuous improvement in system design and solution scalability
Requirements
- Strong solution architecture and system design experience with 9‑14 years in software development
- Expert Python programming skills with production‑grade code quality
- Proficient in microservices, design patterns, FastAPI, Redis, Elasticsearch, and Kafka
- Extensive GenAI application development experience including Agents, MCP, RAG, Agentic RAG, and GraphRAG
- Deep knowledge of LangGraph, LangChain, and orchestration frameworks
- Practical experience in LLM evaluation, RAG evaluation, and prompt management
- Proven track record delivering scalable, production GenAI applications
- Experience with cloud platforms such as AWS, Azure, or GCP
- Familiarity with container technologies Docker and Kubernetes
- Knowledge of vector databases including Pinecone, Weaviate, or Chroma
- Understanding of LLMOps practices and monitoring tools
- Excellent leadership skills to guide engineering teams
- Ability to work collaboratively in a client‑facing environment
- Strong written and verbal English communication skills (B2+)
Nice to have
- Background in traditional machine learning including feature engineering, model training, and evaluation
- Experience with knowledge graphs and fine‑tuning techniques
- Prior consulting or client‑facing role experience
We offer
- Opportunity to work on technical challenges that may impact across geographies
- Vast opportunities for self‑development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
- Opportunity to share your ideas on international platforms
- Sponsored Tech Talks & Hackathons
- Unlimited access to LinkedIn learning solutions
- Possibility to relocate to any EPAM office for short and long‑term projects
- Focused individual development
- Benefit package:
- Health benefits
- Retirement benefits
- Paid time off
- Flexible benefits
- Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)
Requirements
- 9‑14 years of software development experience with strong solution architecture and system design background
- Expert‑level Python programming with production‑grade code quality
- Proficiency in microservices, design patterns, FastAPI, Redis, Elasticsearch, and Kafka
- Extensive GenAI application development experience (Agents, MCP, RAG, Agentic RAG, GraphRAG)
- Deep knowledge of LangGraph, LangChain, and orchestration frameworks
- Practical experience in LLM evaluation, RAG evaluation, and prompt management
- Proven track record delivering scalable, production GenAI applications
- Experience with cloud platforms (AWS, Azure, or GCP)
- Familiarity with Docker and Kubernetes
- Knowledge of vector databases (Pinecone, Weaviate, or Chroma)
- Understanding of LLMOps practices and monitoring tools
- Excellent leadership skills to guide engineering teams
- Ability to work collaboratively in a client‑facing environment
- Strong written and verbal English communication skills (B2+)
Responsibilities
- Design end-to-end GenAI architectures including RAG, Agents, and Multi-Agent Systems for enterprise clients
- Build reusable solution accelerators and reference implementations to standardize delivery
- Lead technical discovery sessions and provide hands‑on guidance to engineering teams
- Define evaluation frameworks and establish best practices for large language model (LLM) applications
- Collaborate with cross‑functional teams to ensure scalable and maintainable system designs
- Implement microservices architectures using design patterns and modern frameworks
- Oversee integration of cloud infrastructure components such as AWS, Azure, or GCP
- Manage containerization and orchestration using Docker and Kubernetes
- Evaluate and select vector databases like Pinecone, Weaviate, or Chroma for GenAI solutions
- Apply LLMOps practices and monitoring to optimize production deployments
- Support prompt management and RAG evaluation to enhance application accuracy
- Contribute to knowledge sharing and mentoring within the architecture group
- Ensure production‑grade code quality in Python applications
- Drive continuous improvement in system design and solution scalability
Benefits
Health benefitsRetirement benefitsPaid time offFlexible benefitsOnline university and external certification learning opportunitiesSponsored tech talks & hackathonsUnlimited access to LinkedIn LearningPossibility to relocate to any EPAM office for short‑ and long‑term projectsForums for CSR, photography, painting, sports, etc.
Skills
PythonFastAPIRedisElasticsearchKafkaAWSAzureGCPDockerKubernetesPineconeWeaviateChromaLangGraphLangChainLLMOpsRAGAgentsMicroservicesDesign patterns
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