TechChefz - Python Architect - Generative AI

<p><p><b>Python Architect - Generative AI</b><br/><br/>Experience : 8-12 Years<br/><br/>We are seeking a visionary Python Architect with a deep foundation in enterprise backend engineering and extensive, hands-on experience in Generative AI at scale.<br/><br/>The ideal candidate will have 8-12 years of core Python development experience, including a significant tenure (at least 2.5 years) focused on architecting and delivering GenAI and microservices in production.<br/><br/>This role is for a senior leader who can define the technical vision, establish architectural standards, and guide multiple engineering teams in building scalable, secure, and robust AI-powered solutions.<br/><br/><b>Primary Responsibilities : </b><br/><br/>- Architectural Leadership : Define and own the architectural roadmap for enterprise-grade Python microservices and GenAI platforms.<br/><br/>- System Design : Design end-to-end GenAI-powered solutions, with a focus on Retrieval-Augmented Generation (RAG) pipelines and sophisticated LLM orchestration engines.<br/><br/>- Technical Governance : Establish technical standards, best practices, and governance for RESTful API design and backend services using FastAPI/Flask, ensuring seamless integration with OpenAI/Azure OpenAI or open-source models.<br/><br/>- DevOps & MLOps Strategy : Collaborate with DevOps and MLOps teams to define and enable a cohesive CI/CD, monitoring, and observability strategy for all GenAI pipelines and services.<br/><br/>- Strategic Collaboration : Partner with ML engineers and data scientists to optimize system-level performance and scalability, ensuring the long-term viability of AI solutions.<br/><br/>- Team Guidance : Lead by example, conducting high-level design reviews, setting architectural direction, and mentoring multiple engineering teams on technical excellence.<br/><br/>- Advanced Orchestration : Drive the adoption and implementation of advanced agentic workflows using frameworks like Semantic Kernel, LangGraph, or other cutting-edge orchestration tools.<br/><br/>- Platform Security : Champion and ensure system reliability, security, and scalability across the entire portfolio of GenAI-enabled services.<br/><br/><b>Core Skills Required : </b><br/><br/>- Python Mastery : Expert-level Python development skills, with deep experience in designing and building with frameworks like FastAPI, Flask, and asyncio.<br/><br/>- Architectural Design : A proven track record of architecting and delivering complex, distributed microservices and systems at enterprise scale.<br/><br/>- GenAI Expertise : In-depth, hands-on experience with GenAI tools, including LangChain, LlamaIndex, Hugging Face Transformers, and their production deployment.<br/><br/>- Cloud Platform Leadership : Extensive experience deploying and managing LLMs on cloud platforms, with a strong preference for Azure OpenAI.<br/><br/>- API & Data Design : Expertise in REST API design, system integration, and advanced use of vector databases like FAISS, Pinecone, or Weaviate.<br/><br/>- DevOps Strategy : Strategic understanding and practical experience with DevOps practices, including CI/CD with GitHub Actions, Docker, Kubernetes, and Terraform.<br/><br/>- Technical Leadership : Demonstrated ability to lead complex technical initiatives and define architectural direction for a group of engineers.<br/><br/><b>Secondary / Nice-to-Have Skills : </b><br/><br/>- Agentic Orchestration : Experience with multi-agent systems and advanced orchestration tools like Autogen or LangGraph.<br/><br/>- LLM Lifecycle Management : Background in fine-tuning, serving, and managing the lifecycle of open-source LLMs in a production environment.<br/><br/>- Observability & Security : Deep understanding of AI observability, security, and performance tuning at a systemic level.<br/><br/>- MLOps & Data Science : A background in MLOps and a proven ability to collaborate effectively with Data Science and ML teams to deliver business value</p><br/></p> (ref:hirist.tech)