Staff Software Engineer, AI Platform & Enablement

Zendesk, Inc.; Ciudad de México; On-site; MXN 1,000,000 - 1,700,000; Full time

Job summary

Zendesk, Inc. is seeking a hands-on software engineer in Mexico City to build and operate backend services and AI-enabled platform assets. You will join the local platform pod, report to the Platform Team Director, and collaborate with global teams to deliver durable, scalable software.

You will design APIs, data models, and integrations, lead production readiness reviews, and contribute to secure, observable systems across time zones. This role does not include people management.

Qualifications

• Bachelor's degree in Computer Science or equivalent.
• 5+ years building and operating backend or platform software.
• Strong programming in Python, Go, or TypeScript/Node.
• Hands-on GCP experience (GKE, Cloud Run, Cloud SQL, IAM, logging).

Responsibilities

• Design, build, and operate backend services, APIs, and cloud infra on GCP.
• Create reusable integration and deployment patterns for teams.
• Guide teams from prototype to production-ready systems with durable designs.
• Develop shared path for reusable AI assets with ownership and auditability.
• Partner with product/value streams on targeted AI use cases.
• Own CI/CD, infrastructure as code, and release practices.
• Improve observability, incident response, and runbooks.

Skills

Python

Go

TypeScript/Node

CI/CD

Security best practices

Education

Bachelor's degree in Computer Science

Tools

Kubernetes

GCP

OpenTelemetry

IAM

Job description

Zendesk is building App Foundry and related internal platforms so employees can turn AI ideas into useful, governed capabilities. Our Co-Build model puts the team closest to a business problem in the builder's seat. The platform team provides the services, reusable patterns, technical guidance, and release controls that help those teams build well and operate what they create.

We are looking for software engineers in Mexico City who can both build production systems and raise the quality of work built by others. You will be a hands-on individual contributor in the local platform pod, reporting to the Platform Team Director and partnering with India-based platform, product, security, identity, and enterprise AI teams. This is an engineering role; it does not include people management.

What you'll do

• Design, build, and operate backend services, APIs, data stores, and cloud infrastructure that support App Foundry and the broader employee AI platform on GCP.
• Create reusable integration and deployment patterns for product teams and business builders, including authenticated APIs, connectors and MCP-backed capabilities where appropriate.
• Help teams move from prototypes to supportable production systems. Review architecture, data choices, access boundaries, dependencies, and operational readiness; explain the tradeoffs and guide teams toward durable designs.
• Build the shared path for submitting, reviewing, versioning, releasing, and maintaining reusable AI assets such as skills, plugins, and connected capabilities. Make ownership, approvals, changes, and deployed state visible and auditable.
• Partner with product and value stream teams on targeted AI use cases. Provide technical advice and co-build support while the delivery team owns the build and the business owner owns the outcome.
• Support function-built productivity assets with platform tooling, templates, documentation, and technical review. Work with product reviewers and workspace administrators on controlled publishing and access verification.
• Own CI/CD, infrastructure as code, automated validation, and release practices. Improve observability, alerting, runbooks, incident response, and durable fixes for the services you own.
• Work with Security, Identity, Enterprise Architecture, and data teams on least-privilege access, secrets, approved data paths, audit logging, and production readiness.
• Make the safe path easy to use: write clear guidance, create examples and paved roads, and help builders learn how to apply them. Give constructive code and design reviews and share what the team learns from pilots and incidents.
• Keep work visible through clear ownership, written updates, documented decisions, and timely escalation across Pune and US time zones.

What you bring

• Bachelor's degree in Computer Science, Information Systems, or equivalent practical experience.
• 5+ years building and operating backend services or platform software in enterprise or SaaS environments.
• Strong programming skills in at least one of Python, Go, or TypeScript/Node, with experience designing APIs, data models, and reliable integrations.
• Hands-on cloud experience, preferably GCP (such as GKE, Cloud Run, Cloud SQL, IAM, and logging), or comparable AWS or Azure experience.
• Experience with infrastructure as code, modern CI/CD, automated testing, and production operations.
• Experience securing APIs and services with authentication, authorization, secrets management, and appropriate logging.
• Sound architectural judgment: you can recognize brittle shortcuts, propose a maintainable path, and help another team implement it without taking ownership of every build.
• Ability to work with product and business partners to clarify a use case, identify its data and integration dependencies, and turn a prototype into a reviewed, supportable capability.
• Clear written communication, constructive technical review, and comfort collaborating across time zones and participating in a shared on-call rotation.

Helpful experience

• Internal developer platforms, App Foundry, Backstage, or similar builder platforms.
• AI application integration patterns, including MCP, gateways, skills, plugins, or agent workflows. Deep ML model development is not required.
• Kubernetes, OpenTelemetry, identity-aware access, or zero-trust patterns.
• Versioned asset repositories, approval workflows, controlled publishing, or software supply chain practices.
• Coaching other engineers or business builders through architecture and production readiness reviews.
• Operating in an environment with formal security, audit, and access controls.

What success looks like

• Teams can use documented platform patterns to build useful capabilities with clear owners and fewer one-off integrations.
• The services you own are reliable, observable, secure, and supportable by the team.
• Prototypes that need to scale reach production through sound architecture, reviewed dependencies, and clear handoffs.
• Reusable AI assets have a traceable path from