We are seeking a Software Engineer (Agentic UX Platform) to architect the interface and validation layer of our greenfield Service-as-Software (SaaS 2.0) platform. While our systems engineer builds the engine, you will design the "cockpit" (UX) and the "crash-test facility" (Validation) . You will be at the forefront of defining the human-AI interface within an AI-Native SDLC. Your mission is to build a flexible, coherent UX that enables users to execute complex workflows and manipulate multi-dimensional sales data with ease. If you are an engineer who believes that a system is only as good as its usability, this is your seat at the table. We encourage driven and motivated individuals who are constantly learning to apply even if you do not meet all of the requested criteria. Why Join Inkeros? At Inkeros, we don't just talk about the future of AI—we provide you with the literal and professional tools to build it. We understand that an engineer is only as effective as their environment, which is why we’ve built our culture around three core pillars: 1. Elite Hardware for Elite Performance We believe that engineers should never be bottlenecked by their hardware. You will be equipped with a top-tier mobile workstation and a world-class desk setup from day one: The Powerhouse : A flagship laptop featuring an NVIDIA RTX GPU and the latest high-performance processor. The Command Center : A dual-monitor setup consisting of two 4K displays, giving you the expansive screen real estate needed for complex system engineering and multi-agent monitoring. 2. Radical Investment in Your Growth The AI landscape changes weekly. To keep you at the absolute cutting edge, Inkeros invests heavily in continuous high-level training. 3. Greenfield Freedom & Influence Most "AI roles" involve bolting a chatbot onto a decade-old legacy system. At Inkeros, you are building a greenfield Service-as-Software platform. The Architect of Interaction: You won't just be "skinning" an app; you will be defining the UI patterns for an entirely new way of building software. Direct Impact: Your work with AI will contribute to us moving fast with AI without breaking the product for our sales and marketing users. High Autonomy : As a member of a lean team, your decisions on engineering tool selection, AI governance, and system design will have a direct and lasting impact on the company’s trajectory. Key Responsibilities Dynamic UX Architecture Build and maintain a modular, flexible frontend - integrating with Python-based frameworks for rapid iteration of workflows and dashboards. AI-Native Validation Platform Architect an automated "testing factory" to validate the accuracy of AI-driven UX workflows, ensuring the platform’s orchestrated user experiences are reliable. MCP UI Integration Design how MCP Resources and Templates are leveraged, providing a "human-in-the-loop" mechanism for auditing and refining AI context. Frontend-Backend Synthesis Collaborate to ensure the modular Python backend seamlessly supports a highly interactive and coherent user experience. Quality Governance Implement automated End-to-End (E2E) validation specifically tailored for non-deterministic AI outputs and just-in-time defined user experiences. Rapid Prototyping Lead the "Service-as-Software" transformation by quickly translating customer feedback into functional UI improvements and flexible data visualizations. Core Technical Foundations Full-Stack Python Proficiency (3+ Years): Mastery of Python 3.x with a focus on building web interfaces and APIs. Frontend Engineering (1+ Year): Strong experience in modern frontend development (Flutter (preferred), React, Vue, or Tailwind) and a deep understanding of User Experience (UX) principles. Testing & Quality Frameworks (1+ Year): Proven track record of building complex validation platforms. Experience with Pytest, Playwright, and automated CI/CD validation. Data Visualization: Experience with data visualization libraries (e.g., Plotly, D3.js, or Altair) to make sales/marketing data "actionable." AI Interface Design: Experience building "Human-in-the-Loop" (HITL) interfaces where users can review, edit, or override AI-generated content or agentic decisions.Desire to work on Agent to UI (A2UI) Protocol in a bidirectional manner (Websockets) Contextual Testing: Knowledge of evaluating LLM outputs for UI consistency - ensuring that AI-generated frontends (Q2UI) or data summaries meet strict brand and logic guidelines. MCP Visualization: Ability to design tools and manage observability data to enable engineers and product leaders "see" the AI reasoning layer. Professional & Soft Skills Design Sensibility: You believe that a tool's power is capped by its usability; you strive for "coherence" in every user flow. Product-Driven Development: A "Customer-First" mindset - you believe that engineering excellence is only as valuable as the user problems it solves, and that the UI must remain flexible enough to pivot based on real-world feedback. Ready to redefine the SDLC? If you are a Python expert who thrives at the intersection of user experience and agentic AI systems, we want to hear from you. #J-18808-Ljbffr