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
Solid 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