Principal Engineer, AI Platform & Runtime
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.
The Role
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 platforms that power intelligent automation, orchestration, and decision-making across our products and internal systems. We are looking for a Principal AI Platform Engineer to help define and build the foundational AI execution layer for the company.
Mission
Build the core AI execution substrate of the company. This role is responsible for designing and scaling the foundational runtime that enables AI agents, orchestration workflows, memory systems, model execution, and policy enforcement to operate reliably, securely, and efficiently at enterprise scale. You will help shape the future of AI infrastructure at Medallia by building the platform capabilities that power autonomous workflows, intelligent assistants, multi-agent systems, and enterprise-grade AI applications across the organization.
Responsibilities
AI Runtime & Agent Infrastructure
Qualifications
Minimum Qualifications
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.
The Role
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 platforms that power intelligent automation, orchestration, and decision-making across our products and internal systems. We are looking for a Principal AI Platform Engineer to help define and build the foundational AI execution layer for the company.
Mission
Build the core AI execution substrate of the company. This role is responsible for designing and scaling the foundational runtime that enables AI agents, orchestration workflows, memory systems, model execution, and policy enforcement to operate reliably, securely, and efficiently at enterprise scale. You will help shape the future of AI infrastructure at Medallia by building the platform capabilities that power autonomous workflows, intelligent assistants, multi-agent systems, and enterprise-grade AI applications across the organization.
Responsibilities
AI Runtime & Agent Infrastructure
- Architect and build the foundational AI runtime platform powering agentic systems and intelligent workflows
- Design scalable agent orchestration frameworks capable of coordinating multi-step, multi-agent execution
- Build long-running workflow execution systems with resiliency, retry semantics, checkpointing, and recovery
- Develop streaming and event-driven AI execution architectures for real-time decisioning and automation
- Define standardized abstractions for AI execution, tool usage, context management, and workflow lifecycle
- Build multi-model routing and inference abstraction layers across commercial and open-source LLMs
- Design cost-aware inference execution systems that optimize latency, quality, throughput, and spend
- Implement intelligent model selection, fallback strategies, caching, and load balancing
- Create prompt lifecycle and version management systems supporting experimentation, governance, and observability
- Develop scalable APIs and SDKs enabling internal teams to rapidly build AI-powered capabilities
- Design enterprise-grade AI memory and context handling systems
- Build retrieval, session persistence, contextual grounding, and state management capabilities
- Develop extensible tool-calling infrastructure enabling agents to safely interact with internal and external systems
- Define patterns for structured reasoning, execution planning, and context propagation across workflows
- Implement guardrails, policy enforcement, and runtime safety controls for enterprise AI systems
- Establish observability standards including tracing, telemetry, runtime analytics, evaluation pipelines, and auditability
- Build highly available, scalable, and resilient distributed systems supporting mission-critical workloads
- Partner with Security, Infrastructure, Product, and Engineering leaders to ensure compliant and secure AI platform operations
- Serve as a technical leader and architect for the company’s AI platform strategy
- Drive engineering excellence, platform standards, and architectural best practices
- Mentor senior engineers and influence cross-functional technical direction
- Evaluate emerging AI infrastructure technologies, frameworks, and runtime patterns
Qualifications
Minimum Qualifications
- 10+ years of software engineering experience building large-scale distributed systems and platforms with expertise in backend systems, cloud-native infrastructure, and platform engineering
- Demonstrated experience designing highly scalable event-driven or streaming architectures
- Demonstrated experience building AI/ML infrastructure, orchestration systems, or developer platforms
- Demonstrated experience working with LLM ecosystems, inference APIs, agent frameworks, and AI workflow systems
- Demonstrated experience with programming skills in one or more languages such as Python, Go, Java, or Rust
- Demonstrated experience with Kubernetes, containers, service orchestration, and distributed runtime environments
- Demonstrated understanding of system reliability, observability, performance optimization, and operational excellence
- Proven ability to lead complex cross-functional technical initiatives
- Fluent in English, oral and written
- Experience building agentic AI systems, autonomous workflows, or multi-agent platforms
- Familiarity with vector databases, retrieval systems, memory architectures, and semantic search
- Experience with prompt engineering, evaluation systems, and AI governance frameworks
- Knowledge of AI safety, policy enforcement, and responsible AI operational practices
- Experience optimizing inference cost, latency, throughput, and model utilization at scale
- Contributions to open-source AI infrastructure or platform ecosystems
- Establish a reliable, scalable, and secure AI runtime platform used broadly across Medallia
- Enable product and engineering teams to rapidly build AI-native experiences on standardized infrastructure
- Improve AI execution reliability, observability, governance, and operational efficiency
- Create reusable platform capabilities that accelerate innovation while maintaining enterprise-grade controls
- Drive architectural consistency and technical excellence across the company’s AI ecosystem
- Help define the foundational AI platform strategy of an industry-leading enterprise SaaS company
- Work on deeply technical, high-impact platform challenges at massive scale
- Influence the future of AI-native product development across the organization
- Collaborate with exceptional engineers, architects, and product leaders solving complex enterprise problems
- Build systems that power real-world AI experiences used by global brands and millions of users worldwide