Senior Backend Software Engineer Python

Senior Backend Software Engineer Python Overview

You would join Anaplan’s Predictive Intelligence engineering group, where the focus is on building the backend systems that support the Syrup platform and the company’s forecasting and predictive products. The team is responsible for the production services behind forecasting, scoring, and data processing, as well as the pipelines and infrastructure that make machine learning and AI capabilities available to enterprise customers. This position is for a senior backend engineer who will contribute across the stack, with a strong emphasis on writing high-quality Python that is reliable, efficient, and easy for the rest of the team to build on.

The role sits within a broader organization that describes itself as customer-focused and innovation-driven. The company highlights its work in AI-infused scenario planning and analysis, and says its platform is used by thousands of global organizations, including many well-known enterprise brands. The engineering culture is presented as collaborative, ambitious, and grounded in shared operating principles, with an emphasis on inclusion, accountability, and continuous improvement.

What you will do

• Design and deliver backend services and APIs that are scalable, resilient, and able to handle failures gracefully across the Predictive Intelligence platform.
• Build and improve the forecasting, scoring, and data processing services that power predictive insights, with attention to speed, scalability, and infrastructure efficiency.
• Produce Python code that is clean, maintainable, and well tested, and help establish engineering patterns that make the codebase easier for the whole team to understand and extend.
• Work alongside data scientists and machine learning engineers to bring models into production and to create the data and inference pipelines needed to support them.
• Take part in on-call support for live services, respond to incidents, and help implement improvements after operational issues are resolved.
• Lead technical design discussions and code reviews, contributing to a higher engineering standard across the team.
• Mentor and support more junior engineers, helping them grow in technical judgment and delivery quality.
• Identify shared platform improvements and drive changes that can benefit several services and teams at once.
• Collaborate closely with backend engineers, data scientists, and platform partners, while reporting to the Director of Engineering for Predictive Intelligence.

What the company is looking for

• Substantial professional experience building backend software in production environments.
• Strong Python skills, with a history of delivering performant, maintainable, and well-tested code in real-world systems.
• Practical experience operating containerized services on Kubernetes in at least one major cloud platform such as AWS, Google Cloud, or Azure.
• Experience with data warehousing or analytics technologies, including tools such as Snowflake, Iceberg, Trino, or Postgres.
• A working understanding of how machine learning and AI systems are run in production, including the data pipelines and model pipelines that support them.
• Evidence that you can work independently, take ownership of important systems, and make progress when requirements are not fully defined.
• Experience being on call for production services and contributing to operational excellence.
• A bachelor’s degree in computer science, engineering, or a related technical field, or equivalent practical experience.

Nice-to-have experience

• Hands-on MLOps experience, including model training pipelines, deployment workflows, and tooling such as MLflow.
• Experience turning data science or research code into stable, observable production services.
• Familiarity with orchestration tools such as Prefect, Airflow, or dbt, along with modern data lake architectures.
• Experience using gradient-boosted tree models, neural networks, or optimization solvers in production.
• Exposure to LLM-based or agent-style application patterns and integration of AI services.
• Background knowledge in forecasting, demand planning, retail, or supply chain domains.

Culture, inclusion, and support

Anaplan says it is committed to diversity, equity, inclusion, and belonging, and believes that an inclusive environment strengthens the business and improves trust with customers and partners. The company states that it welcomes people of all backgrounds and identities, including differences in gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, and other personal characteristics. It also says that candidates and employees with disabilities can request reasonable accommodations for the application process, interviews, essential job duties, and equal access to employment benefits and privileges.

The posting also includes a fraud warning. Anaplan says it does not make offers without a substantial interview process involving recruitment and hiring managers, does not send job offers by email, and uses only official @anaplan.com email addresses. If someone is unsure whether a communication is genuine, the company asks that they contact [email protected] before taking further action.

Application and eligibility details

The application is submitted through Greenhouse and includes standard candidate information fields such as contact details, resume upload, LinkedIn profile, and referral/source information. The form also asks whether you are legally authorized to work in the country where the role is located for any employer, and whether you will now or in the future need visa sponsorship for employment at Anaplan. The page does not state whether sponsorship is offered or unavailable.

The posting is for a role based in Manchester, United Kingdom.

Degree Requirement: Not Specified

Visa Sponsorship May be