Python Developer

Overview Our customer is a multinational corporation with more than a century of history and offices in over 180 countries. Their most ambitious goal at the time is to introduce a range of Reduced‑Risk Products (RRPs). The target audience is more than 1 billion consumers around the globe. IT platform hosts 700+ applications. Intellia's mission is to help the client with the engineering of a comprehensive software ecosystem for a game‑changing IoT product on the margin of innovative consumer experience and cutting‑edge technology. Our teams are involved in the engineering of core platform components for best‑in‑class eCommerce, Digital Marketing and IoT solutions. As an Engineer, you will become a part of Core Architecture Team and be responsible for the architecture, implementation of best practices in our Digital Engineering Enterprise Platform. The Platform is a set of services and internet applications that accelerate the development and delivery of software applications by taking care of common SDLC challenges. The Platform provides access and consumption for engineering teams to a set of services, technologies, practices for their development and for operating their application, ensuring a set of compliance and best practices. Qualifications 4+ years of Python development Agent framework experience (LangGraph, Strands, CrewAI, or equivalent) A2A wire format (JSON‑RPC 2.0, SSE) for sub‑agent delegation Testing frameworks for agent workflows (pytest, LangSmith evaluation) Documentation and pattern library authoring Will be a plus LangSmith tracing and evaluation Responsibilities Design and develop AI agent applications using Python and modern agent frameworks such as LangGraph, Strands, CrewAI, or equivalent. Implement multi‑agent collaboration and delegation patterns across complex workflows. Integrate AI agents with AWS Bedrock foundation models and related AWS AI services. Build agent‑to‑agent communication workflows using A2A protocols, JSON‑RPC 2.0, and Server‑Sent Events (SSE). Develop automated testing strategies for agent behavior, workflow correctness, and system reliability. Create and maintain evaluation frameworks using pytest, LangSmith, and other testing tools. Design reusable components, templates, and pattern libraries for agent development teams. Produce high‑quality technical documentation, implementation guides, and architecture patterns. Collaborate with platform and AI engineering teams to improve agent performance, reliability, and maintainability. Monitor, troubleshoot, and optimize agent workflows in production environments. Support best practices around observability, testing, governance, and AI application lifecycle management. #J-18808-Ljbffr