Staff Engineer

At Zendesk, our focus is helping our customers build great relationships with their customers.

We are looking for a Staff Engineer to join our AI Copilot organisation. AI Copilot is a multi-million ARR product that puts AI directly into the hands of customer service agents and administrators.

Responsibilities

• Drive the technical vision and architecture for the Admin Copilot Conversational backend , LLM orchestration, intent detection, context retrieval, and tool execution.
• Own end-to-end delivery of complex, cross-cutting features , from technical design through implementation, release, and production operation.
• Be a hands-on technical leader: set engineering standards, make key architecture decisions, and ensure the team builds reliable, scalable systems.
• Collaborate closely with ML Scientists, Product Management, Design, and partner engineering teams to shape the product roadmap from a technical perspective.
• Influence technical direction beyond your team , contribute to architecture decisions across the Copilot organisation and adjacent teams.
• Design and improve evaluation frameworks, guardrails, and safety mechanisms for LLM-powered features in production.
• Mentor and grow engineers on the team through technical guidance, code review, and pairing. Raise the bar for engineering quality.
• Identify and address systemic technical risks, performance bottlenecks, and reliability gaps before they become customer-facing problems.

Requirements

• 8+ years of experience in software engineering, with demonstrated technical leadership in backend systems.
• Strong experience designing and building distributed systems at scale , APIs, service architectures, and data pipelines.
• Experience with LLM integration in production systems , orchestration, prompt engineering, evaluation, guardrails, or multi-provider setups.
• Fluent in at least one backend language (Ruby, Python, Go, or similar); working proficiency across multiple languages.
• Deep understanding of cloud infrastructure (AWS), containerised deployments (Docker, Kubernetes), and CI/CD practices.
• A track record of driving technical direction for a team or project , architecture decisions, technical roadmaps, and cross-team alignment.
• Ability to operate effectively with ambiguity , you can break down complex problems, make pragmatic tradeoffs, and move fast without sacrificing quality.
• Strong collaboration and communication skills , you influence through technical credibility and clear articulation of tradeoffs, not authority.

Preferred Qualifications

• Experience building conversational AI or chat-based systems (intent detection, context management, tool use).
• Experience with ML infrastructure: model serving, inference pipelines, or evaluation frameworks.
• Familiarity with ML pipeline tooling (e.g., Metaflow) and experiment tracking (e.g., MLflow).
• Experience with event-driven architectures (e.g., Kafka).
• Experience with SQL and data infrastructure (Snowflake, dbt).
• Experience mentoring or technically leading a team of 3+ engineers.

Tech Stack

• Our code is written in Ruby and Python
• Our servers live in AWS
• Our ML pipelines use Metaflow
• Our data is stored in S3, RDS MySQL, and Snowflake (with dbt for transformations)
• Our services and models are deployed to Kubernetes using Docker
• Heavy usage of LLM technology from multiple providers via our LLM Proxy
• Our conversational backend uses the Vercel AI SDK for LLM orchestration