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Zendesk is hiring a Staff Engineer for its AI Copilot organization to lead the Admin Copilot Conversational backend, focusing on LLM orchestration, intent detection, context retrieval, and tool execution, with end-to-end ownership from design to production. The role is hands-on and leadership-focused, requiring setting engineering standards, making architecture decisions, mentoring engineers, and influencing technical direction across the Copilot teams while collaborating with ML scientists, product, design, and partner engineers. You’ll also design evaluation frameworks, guardrails, and safety mechanisms for production LLM features and proactively address systemic risks and performance bottlenecks. Qualifications include 8+ years in software engineering with backend leadership, experience building distributed systems at scale, production LLM integration, fluency in a backend language (Ruby/Python/Go), strong AWS and container/CI/CD expertise, and a proven ability to operate under ambiguity and communicate tradeoffs. Zendesk emphasizes a hybrid, inclusive culture and equal opportunity employment, notes AI may screen applications, and provides accommodations for applicants with disabilities, including a contact email for accommodation requests.

Zendesk is seeking a Senior Software Engineer for its AI Copilot team to deliver AI-powered features for customer-service agents, taking ownership from design through production in a fast, iterative learning culture. You will own end-to-end features, work with ML scientists/engineers to integrate ML capabilities, contribute to architecture decisions, build scalable backend services and APIs, improve reliability, and mentor junior engineers. Required: 5+ years building/operating large-scale internet apps, fluency in Ruby (Python a plus), experience with distributed systems, REST APIs, AWS, Docker/Kubernetes, and CI/CD, plus ability to adapt to changing priorities and collaborate across disciplines. Preferred: SQL/data infra (Snowflake, dbt), exposure to LLM integration, ML pipelines/tools (Metaflow), event-driven architectures (Kafka), and iterative, metrics-driven product development (A/B tests, feature flags). The role uses a tech stack including Ruby/Python, AWS, Metaflow, S3/RDS/MySQL/Snowflake, and Kubernetes with Docker; Zendesk emphasizes a hybrid, inclusive culture, equal opportunity employment, and accommodations with AI screening in certain cases.