
Software Developer Advocate
1 day ago
We are looking for a skilled Lead Software Architect to join our team and contribute to the design and development of scalable backend services.
- Key Responsibilities:
- - Collaborate in designing and developing scalable backend services and APIs using Python and FastAPI.
- - Build and optimize data models for relational (PostgreSQL, MySQL) & NoSQL databases.
- - Develop resilient asynchronous data pipelines, event-driven systems, and caching (Redis).
- - Contribute to the development of user-facing components for agent configuration and data visualization using JavaScript and React.
- - Spearhead integration of LLMs (OpenAI, Azure OpenAI, HuggingFace, Nvidia NIMs) for autonomous agents.
- - Design and refine advanced RAG pipelines and Vector DBs (Milvus, PGVector, Pinecone).
- - Champion prompt engineering, agentic frameworks (LangChain, LlamaIndex) and tool-calling.
- - Support DevOps initiatives by using Git, Docker, and maintaining CI/CD pipelines.
- - Promote agile methodologies, conduct code reviews, and maintain high-quality documentation.
- - Collaborate with cross-functional teams (product, ML, design) to deliver technical solutions.
- - Mentor junior engineers, contribute to technical strategy, and drive innovation.
- Development:
- - Proven experience in Python development, with a track record of building scalable backend services using FastAPI for RESTful APIs and WebSocket communications.
- - Solid understanding of ORMs, relational database schema design (PostgreSQL, MySQL), and effective use of caching layers (Redis).
- DevOps & Software Engineering Practices:
- - Proficient in version control with Git and containerization with Docker.
- - Strong experience in designing, implementing, and advocating for comprehensive unit tests and other automated testing strategies; commitment to TDD/BDD principles is highly desirable.
- - Proficient in agile development methodologies and conducting thorough, constructive code reviews.
- AI/ML Integration:
- - Experience architecting end-to-end AI applications and integrating LLMs into backend workflows.
- - Practical knowledge of prompt engineering, agentic frameworks (LangChain, LlamaIndex), and tool-calling implementations.
- - Background in designing and deploying RAG pipelines, with experience selecting and using Vector Databases (Milvus, PGVector, Pinecone).
- - Awareness of MLOps practices and tools for model deployment and serving (e.g., NVIDIA Triton, KServe).
- - Understanding of Model Context Protocol (MCP) and Agent-to-Agent Toolkit for advanced agentic workflows.
- Front-End Development:
- - Proficient in React (ES6+), JavaScript and TypeScript for developing intuitive and functional user-facing components specifically for agent configuration, interaction, and data visualization.
- - Solid understanding of HTML5 and CSS3 for structuring and styling these internal interfaces effectively.
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