Technical Architect Python / Gen AI Applications

Architect Python Applications with GenAI Integration We are seeking a highly experienced Architect to drive the architecture and delivery of modern, scalable data applications powered by Generative AI (GenAI). This role focuses on solution design, architectural leadership, and cross-functional collaboration across AI/ML platforms, backend engineering, and cloud-native infrastructure. While hands-on AI/ML development is not expected, candidates must demonstrate deep architectural understanding of the GenAI stack. A strong hands-on background in Python-based application development is essential. Required Experience: 8+ years of experience in software engineering, with a minimum of 4 years in a technical leadership or architecture role.Proven track record in building robust Python-based backend systems, using frameworks such as FastAPI, Flask, or Django.Expertise in microservices architecture, distributed system design, and integration patterns.Strong familiarity with cloud platforms such as AWS, Azure, or GCP, and practical knowledge of AI/ML services like SageMaker, Vertex AI, or Azure ML.Architectural experience with vector databases (e.g., Pinecone, FAISS, Weaviate, Qdrant) for semantic search and RAG pipelines.Understanding of DevOps practices, including Docker, Kubernetes, and infrastructure as code.Knowledge of CI/CD processes, system security, and observability/monitoring frameworks. GenAI & AI/ML Architecture Knowledge: Sound understanding of GenAI system components, including LLM lifecycles, embedding generation, prompt orchestration, and RAG architectures.Ability to architect complete GenAI workflows, from context ingestion and enrichment to inference handling and post-processing.Familiarity with API orchestration, agent-based design patterns, and semantic search strategies.While direct data science work is not required, a strong grasp of AI/ML engineering principles and pipeline design is expected to ensure architecture aligns with model and data needs. .