Associate Backend Software Engineer (Python)

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 backend engineer, you will build and maintain core services across this stack, writing clean, well-tested Python while growing your craft alongside experienced engineers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with backend engineers, data scientists, and platform partners.

Your Impact

• Build and maintain backend services, APIs, and data processing components across the Predictive Intelligence stack.
• Contribute to the forecasting, scoring, and data processing services that deliver predictive insights, with attention to performance, reliability, and code quality.
• Write clean, well-tested, maintainable Python and follow established engineering best practices.
• Work with data scientists and ML engineers to integrate models into production services and support the pipelines around them.
• Participate in code reviews and design discussions, and incorporate feedback to grow as an engineer.
• Take part in on-call rotations as you ramp, and help monitor, diagnose, and resolve issues across services and pipelines.
• Collaborate across the team to deliver well-scoped features end to end.

Your Qualifications

• Proven commercial professional software engineering experience building backend services.
• Solid proficiency in Python, with experience writing well-structured, tested production code.
• Experience with relational databases and SQL (e.g., Postgres); familiarity with data warehousing technologies such as Snowflake is a plus.
• Exposure to containerized services and at least one major cloud (AWS, GCP, or Azure).
• Basic understanding of how ML and AI systems run in production and the data pipelines that support them.
• Familiarity with version control (Git) and collaborative development practices.
• Demonstrated ability to take ownership of well-scoped systems and deliver against requirements with some ambiguity.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Preferred Skills

• Experience with data orchestration tools (e.g., Prefect, Airflow, dbt).
• Familiarity with MLOps tooling such as MLflow, or experience supporting ML workloads in production.
• Exposure to LLM or agentic application patterns and AI service integration.
• Experience operating services on Kubernetes.
• Background in forecasting, demand planning, or retail/supply chain domains.