Director, Software Engineering

Zendesk Zendesk · Enterprise · San Francisco, CA +1

Director of Software Engineering to lead and scale global Platform engineering teams, driving the architecture and delivery of API-first, cloud-native platform services that enable partners and customers to build intelligent, AI-powered experiences at scale. The role involves defining platform strategy, owning architecture, partnering with AI teams, driving operational excellence, and staying current with AI tools and technologies.

What you'd actually do

  1. Lead and grow multiple scrum teams, distributed in US and APAC regions, focused on building Technology Platform products for external customers; set priorities, remove blockers, and ensure predictable delivery.
  2. Define technical and product-aligned platform strategy (API-first, extensibility, security, scale) and translate it into roadmaps and execution plans.
  3. Own architecture and engineering decisions for web services, RESTful APIs, SDKs, and integration points with internal/external ecosystems.
  4. Partner closely with Product, Design, Security, and AI teams to deliver features that enable AI agentic actionability and cross-system interactions.
  5. Drive operational excellence (SLA/SLOs, observability, scalability, incident management, CI/CD) to maintain high availability and performance for external customers.

Skills

Required

  • Proven leader who has successfully managed multiple globally distributed scrum/Agile teams delivering platform or external-facing products.
  • Deep hands-on expertise with modern web development stacks, RESTful API design, and frameworks (examples: React/TypeScript, Node/Express, Java/Spring, Go, or equivalent).
  • Strong familiarity with AI tools, technologies, and integration patterns (AI coding, LLMs, RAG, vector embeddings, agent frameworks, model APIs) and their operational requirements.
  • Experience designing and operating cloud-native, microservices-based architectures (Kubernetes, serverless, containerization).
  • Track record of partnering with product and customer-facing teams to deliver usable, extensible APIs and SDKs.
  • Excellent communicator and mentor; comfortable presenting technical strategy to executives, senior stakeholders and customers.
  • Bias for data-informed decisions and strong focus on reliability, security, quality, customer health, and developer experience.
  • 10+ years total software engineering experience, including a minimum of 5 years leading multiple scrum teams building technology platform products for external customers.
  • Hands-on experience designing and shipping RESTful APIs and web applications with one or more modern frameworks and languages.
  • Demonstrated experience integrating AI/ML capabilities into production systems or enabling AI-driven products.
  • Proven success operating cloud-native distributed systems at scale (Kubernetes, cloud providers, CI/CD, observability).

Nice to have

  • Prior Director-level leadership in a SaaS or platform company, delivering external-facing developer platforms or partner integrations.
  • Practical experience with agent frameworks and protocols that enable agentic behavior (e.g., orchestration patterns, tool-use, safety/guardrails).
  • Strong background in developer experience (API design, SDKs, docs, developer tooling) and/or platform product management.
  • Advanced degree in Computer Science or related field, or equivalent industry experience.
  • Experience with security, privacy, and compliance considerations for external platforms (OAuth, mTLS, data governance).

What the JD emphasized

  • AI agentic actionability
  • AI tools, technologies, and protocols
  • AI coding, LLMs, RAG, vector embeddings, agent frameworks, model APIs
  • integrating AI/ML capabilities into production systems
  • agent frameworks and protocols that enable agentic behavior

Other signals

  • leading global platform engineering teams
  • API-first, cloud-native platform services
  • enable partners and customers to build intelligent, AI-powered experiences at scale
  • connecting those capabilities to our AI and ecosystem strategies
  • deliver features that enable AI agentic actionability and cross-system interactions
  • architectural and technology initiatives for high-throughput, low-latency, globally distributed Platform systems and services
  • leverage and evaluate AI tools, technologies, and protocols (Claude coding, Cursor, LLMs, embeddings, RAG, Agent frameworks, orchestration protocols)