Job Description
Design, develop, and maintain scalable Python-based APIs and backend services using FastAPI and related frameworks. Build, deploy, and optimize production-grade LLM applications using providers such as OpenAI and Anthropic. Design and implement end-to-end RAG solutions, including vector databases, semantic search, retrieval optimization, and chunking strategies. Develop and manage secure, scalable MCP servers and AI infrastructure. Build and orchestrate multi-agent systems to automate complex workflows and business processes. Create, test, and refine prompts, agent instructions, and LLM interactions to improve solution quality and performance. Leverage AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate software delivery and engineering efficiency. Implement event-driven architectures, messaging systems, and real-time communication patterns. Monitor, troubleshoot, and optimize AI and backend systems for performance, reliability, scalability, and security. Collaborate with cross-functional teams to deliver innovative AI solutions and establish engineering best practices. 8+ years of experience developing APIs with Python 2+ years of experience developing and experimenting with LLMs Hands-on, daily use of AI-assisted and agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot, autonomous coding agents) to write and refactor code, automate workflows, and optimize engineering processes. Strong experience with Python, particularly in building REST APIs using frameworks like FastAPI. Grounding in NLP and machine learning as they relate to building LLM systems Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) Experience building, deploying, and securing MCP servers at scale. Understanding of multi-agent systems and their applications in complex problem-solving scenarios. Designing and implementing RAG systems end to end: vector databases, semantic search, retrieval quality, and chunking strategy. Experie
