Our team is expanding, and we're bringing on a Solution Architect with deep specialization in Python and Generative AI to build and deliver enterprise-grade GenAI solutions ready for real-world production use. You'll be an integral part of our Solution Architecture group, spearheading technical exploration efforts, crafting reusable frameworks, and shaping standards for LLM-based applications. Submit your application to take part in forward-thinking GenAI initiatives and empower clients to achieve breakthrough outcomes.

Responsibilities

- Architect complete GenAI systems, including RAG frameworks, Agents, and Multi-Agent configurations, tailored for enterprise-level clients
- Develop reusable accelerators and reference builds to bring consistency to delivery approaches
- Facilitate technical discovery workshops while offering direct, practical support to engineering teams
- Establish evaluation methodologies and set standards for building large language model (LLM) applications
- Work alongside diverse teams to guarantee system designs that scale effectively and remain easy to maintain
- Build out microservices-based architectures leveraging established design patterns and contemporary frameworks
- Manage the incorporation of cloud infrastructure elements across platforms like AWS, Azure, or GCP
- Handle containerization and orchestration processes utilizing Docker and Kubernetes
- Assess and choose suitable vector database solutions, such as Pinecone, Weaviate, or Chroma, for GenAI use cases
- Deploy LLMOps methodologies and monitoring solutions to fine-tune production-level deployments
- Assist with prompt management and RAG evaluation processes to boost application precision




- Take part in mentoring efforts and knowledge exchange across the broader architecture team
- Maintain high standards of production-ready code quality within Python-based applications
- Push forward ongoing enhancements in system architecture and solution scalability

Requirements

- Between 9 and 14 years of experience in software development, with a strong foundation in solution architecture and system design
- Advanced Python development skills with a focus on writing production-ready code
- Skilled in microservices design, architectural patterns, FastAPI, Redis, Elasticsearch, and Kafka
- Substantial background building GenAI applications, covering Agents, MCP, RAG, Agentic RAG, and GraphRAG
- Strong familiarity with LangGraph, LangChain, and related orchestration tools
- Hands-on background in evaluating LLMs and RAG systems, along with managing prompts
- Demonstrated success in delivering scalable GenAI applications ready for production environments
- Working experience with cloud ecosystems such as AWS, Azure, or GCP
- Comfortable with containerization tools, namely Docker and Kubernetes
- Familiarity with vector database technologies, including Pinecone, Weaviate, or Chroma
- Solid grasp of LLMOps principles and associated monitoring solutions
- Robust leadership capabilities suited to directing engineering teams
- Capacity to thrive in client-facing settings while working collaboratively
- Solid English communication skills, both written and spoken, at B2 level or above

Nice to have

- Experience in conventional machine learning practices, including feature engineering, model training, and evaluation methods
- Familiarity with knowledge graphs along with fine-tuning approaches
- Previous background in consulting positions or client-facing capacities

📌 Solution Architect – Python (Bengaluru)
🏢 EPAM Systems
📍 Bengaluru