Senior Backend Software Engineer (Python)

At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market. What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture. Our customers rank among the who’s who in the Fortune 50.

Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform. Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating our wins – big and small.

Supported by operating principles of being strategy-led, values -based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together! You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the Syrup platform and Anaplan’s forecasting and predictive solutions.

The team owns the production services behind forecasting, scoring, and data processing, along with the pipelines and infrastructure that bring ML and AI capabilities to enterprise customers. As a senior backend engineer, you will design and build core services across this stack — writing clean, performant, well-tested Python that the rest of the team can build on. This role reports to the Director of Engineering for Predictive Intelligence and works closely with backend engineers, data scientists, and platform partners.

Your Impact Design and implement scalable, fault-tolerant backend services and APIs as a core contributor across the Predictive Intelligence stack. Build and evolve the forecasting, scoring, and data processing services that deliver predictive insights, with a focus on performance, scalability, and cost efficiency. Write clean, well-tested, maintainable Python and establish patterns that make the codebase easier for the whole team to extend, operate, and reason about.

Partner with data scientists and ML engineers to integrate models into production services and build the data and inference pipelines around them. Take part in on-call rotations and own the operational health of high-availability production services, including incident response and post-incident improvements. Lead design reviews and code reviews, raising the quality bar across the team and mentoring mid-level and junior engineers.

Identify and drive cross-cutting platform improvements that benefit multiple services and teams.

Qualifications

Extensive professional software engineering experience building production backend services. Strong proficiency in Python, with a track record of writing performant, well-tested, maintainable production code. Hands-on experience operating containerized services on Kubernetes in at least one major cloud (AWS, GCP, or Azure).

Experience with data warehousing or analytics technologies such as Snowflake, Iceberg, Trino, or Postgres. Working understanding of how ML and AI systems run in production, including the data and model pipelines that support them.

Requirements

Track record of being on-call for production services and contributing to operational excellence. Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Preferred Skills Hands-on MLOps experience, including model training pipelines, deployment workflows, and tooling such as MLflow.

Experience productionizing data science or research code into stable, observable services.