Staff Software Engineer - Ruby

• Provide technical leadership across multiple teams, setting architectural direction and raising the bar for engineering quality and delivery practices.
• Work closely with ML Scientists and ML Engineers to bring ML-powered capabilities into production as polished product features that customers use daily.
• Own the design and architecture of complex, cross-cutting systems - driving decisions from proposal through to production, and iterating based on real usage.
• Identify and drive high-impact technical initiatives: performance, scalability, cost optimisation, and developer productivity.
• Collaborate with Product Management, Design, and engineering leadership to shape the technical roadmap and ensure engineering investments align with product and business goals.
• Mentor and elevate engineers across the organisation - through code review, design reviews, pairing, and setting strong technical standards.
• Be a bridge between product engineering and ML/science - you understand both worlds well enough to make pragmatic trade-offs that get features shipped.

• 10+ years of experience building, scaling, and operating large-scale, Internet-facing applications, with a demonstrated ability to set technical direction across teams.
• Fluent in Ruby; working proficiency in Python is a big plus.
• Strong experience with distributed systems, RESTful APIs, event-driven architectures (e.g., Kafka), and cloud infrastructure (AWS).
• Deep experience with containerised deployments (Docker, Kubernetes) and CI/CD practices.
• Proven ability to lead cross-team technical initiatives from conception to delivery - you ship, you don't just design.
• Comfort working alongside ML engineers and scientists: you don't need to train models, but you understand ML workflows, model serving, LLM integration patterns, and how to build reliable product experiences on top of ML capabilities.
• Strong experience with SQL and data infrastructure - you can reason about data pipelines, query performance, and analytics.
• Ability to navigate ambiguity, make sound trade-offs, and provide direction when priorities shift.
• A track record of mentoring engineers and raising the technical bar across an organisation.

Preferred

• Experience with Snowflake and dbt for data transformations and analytics - this is a significant part of our data infrastructure.
• Hands-on experience integrating LLMs into production systems: prompt engineering, evaluation, monitoring, cost management, and multi-provider strategies.
• Familiarity with ML pipeline tooling (e.g., Metaflow) and ML frameworks.
• Experience with iterative, metrics-driven product development (A/B testing, feature flags, incremental rollouts).
• Background in building AI/ML-powered products where the ML capability is embedded in a broader product experience.

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

Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.

At Zendesk, our focus is helping our customers build great relationships with their customers. Founded by three Danish entrepreneurs, Zendesk has experienced remarkable success and growth while maintaining a fun, positive, and down-to-earth culture. We are looking for a Staff Software 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. You will be a technical leader across teams, driving the architecture and delivery of AI-powered product features at Zendesk scale. We ship to learn: our philosophy is to deliver early, deliver often, and iterate based on real-world customer feedback. We're looking for engineers who lead by example in turning ambiguity into shipped product., Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love. Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.