Description
Electronic Arts creează experiențe de divertisment de următorul nivel, care inspiră jucătorii și fanii din întreaga lume. Aici, toată lumea face parte din poveste. Face parte dintr-o comunitate care stabilește legături în întreaga lume. Un loc în care creativitatea prosperă, sunt încurajate noi perspective, iar ideile sunt importante. O echipă în care toată lumea face jocul posibil.
In FC Quality Verification Engineering, our mission is to build the technology, large-scale test automation, and AI-powered developer tools that help our EA SPORTS FC teams understand game quality and decide when we are ready to ship. We work closely with development, quality verification, production, content, and live operations teams.
As a Senior Software Developer in Vancouver you will manage these systems from proposal to adoption. You will shape our technical direction, write code, define success metrics, and mentor engineers on our team. You will report to our Technical Director, FC Quality Verification Engineering. You will work hybrid, at least 3 days a week, from our office in Burnaby, BC.
Responsibilities:
- 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-personalization systems.
- Develop distributed agent execution environment that autonomously run and self-heal 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 our Continuous Integration and Continuous Delivery (CI/CD) workflows and distributed execution services.
- Diagnose failures across code, data, and infrastructure, fix root causes, and mentor our engineers through code reviews and knowledge sharing.
- Act as product owner for the systems you lead: work with stakeholders to define and prioritize 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.
Required qualifications:
- 10+ years of professional software development experience.
- A Batchelor 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.