Senior AI Data Engineer, Copilot
Description
Job Description
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 Senior AI Data 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 — powering real-time suggestions, automated actions, and proactive insights. You will build and scale the data infrastructure that underpins these AI/ML features, ensuring our solutions are accurate, cost-efficient, and continuously improving as we grow.
We ship to learn: our philosophy is to deliver early, deliver often, and iterate based on real-world customer feedback.
What you'll be doing
Design, build, and maintain scalable ELT pipelines that power AI Copilot's ML-driven features.
Build data infrastructure that enables real-time, contextually relevant AI capabilities and continuous learning at scale.
Collaborate closely with ML Scientists and Engineers to support model experimentation, evaluation, and production deployment for LLM-powered features.
Build and optimise SQL-based data models using dbt to enable AI insights, analytics, and self-service ROI measurement.
Implement cost optimisation strategies for large-scale AI data pipelines — driving down operating costs while maintaining quality and reliability.
Create data infrastructure to support ML model monitoring, evaluation, and key product metrics.
Contribute to the team's technical vision for building a self-improving AI product that gets better as it scales.
Work with feature teams, platform teams, and product to ensure reliable data foundations for AI capabilities.
What you bring to the role
Required
5+ years of data engineering experience building, maintaining, and working with data pipelines and ELT processes in big data environments.
Extensive experience with SQL, ideally in the context of data modelling and analysis.
Hands-on production experience with dbt, and proven knowledge in modern and classic data modelling (Kimball, Inmon, etc.).
Fluent in Python; exposure to Ruby is a plus.
Experience with Snowflake or other cloud columnar databases (Amazon Redshift, Google BigQuery).
Previous experience working with AI/ML products and understanding of ML workflows.
Proven experience in performance testing, capacity planning, and cost optimisation for large-scale data pipelines and systems.
Experience with Kafka, Docker, Kubernetes, and cloud platforms (AWS).
Ability to work with uncertainty and the flexibility to pivot with changing priorities.
Strong collaboration skills and a genuine desire to help the team succeed.
Preferred
Experience with Metaflow for ML pipeline orchestration.
Experience with LLM evaluation and monitoring tooling.
Experience with experiment tracking tools (e.g., MLflow).
SnowPro Core certification or equivalent hands-on expertise.
Hands-on production experience with Apache Spark (Spark SQL / PySpark).
Familiarity with Tableau or Looker for BI and analytics visualisation.
Experience building data infrastructure for product-led growth and self-service analytics.
Tech Stack
Our code is written in Python and Ruby
Our servers live in AWS
Our ML pipelines use Metaflow
Our experiment tracking uses MLflow
Our data is stored in S3, RDS MySQL, and Snowflake (with dbt for transformations)
Our ELT stack includes dbt and Kafka
Our services and models are deployed to Kubernetes using Docker
Heavy usage of LLM technology from multiple providers
BI tools include Tableau and Looker
Infrastructure managed with Terraform and GitHub Actions
#LI-AO1
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.
The intelligent heart of customer experience
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.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.