Principal Architect, AI-Native Platform Transformation

Overview

Medallia is the pioneer and market leader in Experience Management. Our award‑winning SaaS platform, Medallia Experience Cloud, leads the market in the management of experiences, insights, and actions for candidates, customers, employees, patients, and residents alike.

We believe that every experience is a memory that can last a lifetime. Experiences shape the way people feel about a company. And they greatly influence how likely people are to advocate, contribute, and stay. At Medallia, we are committed to creating a world where organizations are loved by their customers and their employees.

We empower exceptional people to create extraordinary experiences together.

Bring your whole self.

At Medallia, we believe every experience is a memory that can inspire loyalty, trust, and growth. Our platform helps the world’s leading brands capture signals across customer and employee journeys and transform them into real‑time action using AI and analytics at enterprise scale. We are building the next generation of AI‑native platform capabilities that power intelligent automation, orchestration, and decision‑making across our products and we need an architect to ensure that evolution happens coherently.

As the Principal Architect, you will own the end‑to‑end architectural transformation of Medallia from traditional enterprise software into an AI‑native platform company. AI technology and innovation are advancing at a remarkable pace, and we are building AI capabilities across every part of our platform. Your mission is to establish the architectural patterns and practices that ensure this work compounds toward a platform vision rather than fragmented features.

Define the Enterprise AI Reference Architecture, draw the boundaries between centralized platform capability and product‑owned innovation, and drive the organizational convergence that makes the platform evolve as one system over the next 3–5 years aligned to emerging standards for AI systems and agent protocols. You are the architect who sees around corners and where the world is going, anticipating what the platform must become when agents, not humans, are the primary actors.

Define the Enterprise AI Reference Architecture

• Establish standardized agent runtime patterns: orchestration frameworks, agent lifecycle management, and execution environments that product teams build on rather than reinvent.
• Define the memory and context architecture: how customer, session, and domain context is structured, persisted, shared, and scoped across agents and products.
• Set standards for agent communication and interoperability (MCP, A2A, and emerging protocols), eventing, and multi‑agent coordination patterns.
• Design the model abstraction layer: provider‑agnostic interfaces, routing and fallback strategies, and the portability architecture that preserves negotiating leverage and cost flexibility.
• Establish observability and evaluation standards for non‑deterministic systems: tracing, eval harnesses, quality gates, and cost telemetry as first‑class architectural concerns.

Set AI Platform Strategy

• Draw and defend the strategic boundary between centralized platform capabilities (runtimes, model gateway, context services, eval infrastructure) and what remains product‑owned, with clear interface contracts between the two.
• Lead build vs. buy decisions across the AI stack and formulate the vendor abstraction strategy that prevents lock‑in at the model, framework, and infrastructure layers.
• Own the platform consolidation roadmap: sequence the convergence of overlapping AI implementations onto shared services without freezing product velocity.
• Maintain the architectural decision record for the AI platform, making trade‑offs explicit, durable, and revisit able as the landscape shifts.

Drive Organizational Convergence

• Serve as the primary architectural liaison across Product, Engineering, Data, Security, Infrastructure, Applied AI, and Enterprise Architecture.
• Run the architectural review and exception process for AI initiatives: a lightweight governance mechanism that catches divergence early without becoming a bottleneck.
• Identify and dismantle fragmented…