Python Developer (Agentic AI & LLMs)

What You'll DoDesign and build new capabilities for the AI assistant — from idea to production.Build the agentic core: LLM-driven reasoning that decides what to do, calls the right tools, and runs multi-step workflows.Design how multiple specialized agents and steps coordinate to handle complex requests.Integrate the assistant with data sources, internal APIs, and external tools through function/tool calling.Build and refine conversation memory and context handling, so the assistant follows up naturally across a conversation.Expand the range of questions the assistant can handle and the depth of its answers.Keep answers grounded in real data — a principle we build to.Build responsive, intuitive web interfaces using React.js / Next.js for AI-powered experiences.Develop and integrate chat, conversational, and AI-driven UI components with backend services and APIs.Improve the speed, cost, scalability, and stability of the system as it grows.Use evaluation and monitoring to maintain high-quality AI responses as the product evolves.Deploy, monitor, troubleshoot, and support the assistant in production.Partner with product owners, data teams, and stakeholders to turn business requirements into working features.What We Are Looking For3+ years of professional software development experience, with strong backend experience in Python.Strong hands-on experience with Python and backend frameworks such as FastAPI, Django, or Flask.Strong hands-on experience with React.js and Next.js for building modern, production-grade web applications.Real hands-on experience building applications with LLMs — production experience preferred, not just prototypes.Hands-on experience designing agentic AI systems, including tool/function calling, workflow orchestration, and multi-agent coordination.Good understanding of prompt design, conversation memory, and context management.Familiarity with retrieval and semantic search, including embeddings and vector databases, and an understanding of when to use them.Familiarity with an AI agent/orchestration framework such as LangChain, LlamaIndex, LangGraph, or similar.Experience integrating frontend applications with REST APIs, AI services, streaming responses, and real-time conversational experiences.Experience running APIs and services in production on a major cloud platform such as AWS, Azure, or GCP.Strong understanding of software architecture, API design, debugging, testing, and performance optimization.A strong ownership mindset — able to drive a feature from design to production with limited hand-holding.A clear communicator who's comfortable working directly with product teams and stakeholders.Nice To HaveExperience building AI applications on top of large, real-world datasets.Experience with voice or conversational interfaces.Experience with streaming AI responses / real-time AI interactions.Experience with .NET / ASP.NET Core — part of our stack uses it.Experience with Docker, CI/CD, observability, and production AI infrastructure.Experience working with vector databases and modern data/AI infrastructure.