Engineering Jobs in Buenos Aires, Argentina (Now Hiring) — 287 open — Page 12

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

• 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

Model Orchestration & Inference Platform

• 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

Memory, Context & Tooling Systems

• 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

Governance, Reliability & Security

• 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

Technical Leadership

• 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

 

Candidates based in the Buenos Aires vicinity will be prioritized as this role is Hybrid, 3 days per week onsite.

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

Preferred Qualifications

• 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

 

What Success Looks Like

• 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

Why Join Medallia

• 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

 

 

At Medallia, we celebrate diversity and recognize the value it brings to our customers and employees. Medallia is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age (40 and over), disability, genetic information, veteran status or military service, or any other status protected by state or local law. Individuals with a disability who need an accommodation to apply please contact us at [email protected]. For information regarding how Medallia collects and uses personal information, please review our Privacy Policies. Applications will be accepted for 30 days from the date this role was posted or until the role has been filled.