Senior Software Engineer — Matching (Canada)

Backstory helps companies understand the state of their revenue business by answering questions that span customer interactions, sales activity, pipeline health, and deal execution. The platform operates over trillions of sales activities, millions of deals, and more than 160 million business contacts, giving customers a unified view of the signals that drive revenue. Companies such as Nvidia, OpenAI, AMD, Red Hat, and Databricks rely on Backstory to surface risks, identify opportunities, and understand what's happening across their business.

Backstory is building AI systems that reason over massive amounts of enterprise data to help business leaders understand what's happening in their business and what to do next. We work at the intersection of large language models, retrieval, evaluation, distributed data systems, and product design, turning billions of signals from across the enterprise into insights people can trust. The underlying challenges span reasoning, search, ranking, data quality, knowledge representation, and operating AI systems against continuously evolving real-world information.

As a Senior Software Engineer on the Matching team, you will work on Backstory's foundational technology — matching business activities to business context. You will handle a vast amount of business data, perform data-driven research, design and develop algorithms and microservice architecture, write machine learning and automation code, and build scalable systems that power the AI-engine behind Backstory's products.

We value ownership highly — the ability to take an idea through all the stages from conception to shipping a product. This reflects throughout our company, but is especially true in engineering. As an engineer at Backstory, you'll be a part of a highly independent and autonomous team. Since we're building out a robust data layer that needs to be presented elegantly to the end-user, you'll be working with a large array of different technologies and fields. Expect lots of interesting challenges.

Responsibilities

• Design and implement core backend services and data pipelines
• Perform data-driven research using big data and leveraging Data Science toolset
• Document design choices and operational knowledge to successfully deploy and run services
• Provide appropriate test coverage, unit and integration testing, with focus on performance and cost efficiency for your feature ownership areas
• Ensure robust alerting, dashboards, and runbooks for production services are in place
• Collaborate within the team and with other engineering teams to build new features and products according to business needs
• Follow software design and development best practices and promote such practices in the team

Requirements

• 5+ years of professional experience working on backend systems in an enterprise environment
• 3+ years experience with data analysis / data science tasks and/or ML
• 2+ years experience programming in Python 2.x/3.x or Scala or Java
• Experience with AI development tools (especially agentic AI) is a plus
• Experience developing systems based on LLM is a plus
• Understanding of SOA, microservices, and event-driven architecture
• Experience with an enterprise-grade stack for scalable web apps including messaging broker, in-memory storages, NoSQL, and key-value databases
• Strong knowledge of TDD, Unit, and automated test paradigms
• Experience with SQL and RDBMS solutions
• Experience with large-scale data processing (Spark)

Headquartered in San Francisco, CA, Backstory is backed by Y Combinator and Silicon Valley’s top investors, including ICONIQ Capital, Andreessen Horowitz, Lightspeed Venture Partners, Akkadian Ventures, and Mubadala Capital. Backstory is listed in the top 20 percent of Inc 5000 companies, is a regular leader in our key categories on G2, and is on the Forbes list of America’s Best Startup Employers. For more information, please visit

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.