Senior Software Engineer

In FC Quality Verification Engineering, the mission is to build the technology, large-scale test automation, and AI-powered developer tools that help EA SPORTS FC teams understand game quality and decide when they are ready to ship. The role will manage these systems from proposal to adoption, shaping technical direction, writing code, defining success metrics, and mentoring engineers. It reports to the Technical Director, FC Quality Verification Engineering, and works closely with development, quality verification, production, content, and live operations teams.

• Manage systems from proposal to adoption, shaping technical direction, writing code, and defining success metrics.
• Lead the design and implementation of closed-loop, multi-agent state machines, human-in-the-loop execution flows, and Generative AI testing frameworks for hyper-personalisation systems.
• Develop a distributed agent execution environment that autonomously runs and self-heals end-to-end tests across complex environments.
• Develop statistical validation solutions, probabilistic rubrics, and calibration frameworks to measure feature quality, model drift, and non-deterministic agent behaviour at scale.
• Own technical designs, build reusable components, and improve Continuous Integration and Continuous Delivery (CI/CD) workflows and distributed execution services.
• Diagnose failures across code, data, and infrastructure, fix root causes, and mentor engineers through code reviews and knowledge sharing.
• Act as product owner for the systems the role leads, working with stakeholders to define and prioritise requirements, agree scope and success criteria, turn them into delivery plans, and keep partners informed of estimates, progress, risks, and dependencies.
• Learn and evaluate new engineering approaches, including AI-assisted workflows where useful, and measure improvements in reliability, feedback speed, and adoption.

• 10+ years of professional software development experience.
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field that includes coursework or academic exposure to Artificial Intelligence / Machine Learning concepts.
• Proficiency in C or C++ and Python, alongside experience designing complex software systems, automated testing, and version control.
• Experience designing and independently implementing complex software systems, including interfaces, dependencies, and documented trade-offs.
• In-depth experience with LLMs, multi-agent orchestration, state machines, context/memory management, and human-in-the-loop workflows.
• Proficiency in statistical inference, hypothesis testing, variance reduction, and experimental design to build statistical testing solutions for probabilistic systems.
• Experience developing evaluation frameworks for generative systems, including dataset curation, LLMs-as-a-judge design, validation criteria, error analysis, and quantitative/qualitative metrics.
• Experience building test automation or developer tools, integrating them into CI/CD workflows, and debugging distributed systems using logs and telemetry.

• Hybrid working, with at least 3 days a week from the office in Burnaby, BC.

• Vacation: 3 weeks per year to start.
• 10 days per year of sick time.
• Paid top-up to EI/QPIP benefits up to 100% of base salary when welcoming a new child (12 weeks for maternity, and 4 weeks for parental/adoption leave).
• Extended health, dental, and vision coverage.
• Life insurance.
• Disability insurance.
• Retirement plan for regular full-time employees.
• Certain roles may also be eligible for bonus and other incentive programmes.