About the Project :
We are seeking a Lead Python Engineer (Generative AI) to architect and develop an enterprise-grade, multi-tenant AI assistant that enhances internal company support operations. The platform will leverage Flask, MongoDB, and Googles Gemini AI to provide intelligent, context-aware answers to employees in real time. Development will be executed in a Dockerized environment with PyCharm as the primary IDE.
Key Responsibilities :
- Flask Backend Development : Design, implement, and maintain scalable RESTful APIs, authentication flows, and multi-tenant logic.
- AI Orchestration & Integration : Build and optimize the AI orchestration layer to manage query flows, integrate Gemini AI SDK, and implement intelligent tool-selection mechanisms.
- AI Tools & Services : Develop backend services (e.g., services.py) that enable the AI assistant to fetch real-time employee-specific data such as leave balances, expense statuses, and approvals.
- Database Engineering : Design and optimize MongoDB queries for user management, data ingestion, and low-latency lookups.
- Environment Management : Configure and troubleshoot Docker / Docker Compose environments. Maintain dependencies via requirements.txt.
- Debugging & Optimization : Leverage PyCharms advanced features for profiling, debugging, and code optimization across the stack.
- Collaboration & Best Practices : Enforce coding standards, participate in code reviews, and mentor team members on Python and AI-driven application development.
Required Skills :
Expert-level Python development with hands-on experience in Flask.Strong knowledge of MongoDB or other NoSQL databases.Proficiency with Docker / Docker Compose in enterprise environments.Advanced debugging and troubleshooting skills using PyCharm or equivalent IDE.Proven ability to design scalable, modular, and maintainable systems.Preferred Skills :
Familiarity with Generative AI concepts such as RAG (Retrieval-Augmented Generation) and Tool-Calling.Experience in architecting or scaling multi-tenant SaaS applications.Exposure to enterprise-grade AI chatbots or conversational AI platforms.Working knowledge of cloud-based deployment (AWS, GCP, or Azure).(ref : hirist.tech)