The Infrastructure and Platform Services team (IPS) is the backbone of EA’s global gaming ecosystem, delivering the technology that powers EA’s live games and player experiences. IPS provides a deep portfolio of digital platform gaming services and production infrastructure to EA's game studios. From scalable cloud solutions to AI-driven gameplay services, IPS ensures that EA’s games are available anytime, anywhere for millions of players worldwide.

As a Software Engineer on our team, you will report to the Senior Director of Engineering. You will collaborate with studios to develop internal tools that shape gameplay, progression, and live services. You will maintain an AI-first mentality, finding opportunities to integrate AI and automation into our development lifecycle and product features. You will guide best practices and mentor engineers to provide solutions that support our player-first mission.

Responsibilities:

• Write testable and scalable code across the stack, integrating AI-driven logic into tools used by Live Teams.

• Implement AI capabilities, such as LLM integrations and vector databases, to remove developer bottlenecks and improve tool intelligence.

• Design components and microservices to ensure our stack supports evolving AI technologies.

• Partner with game designers and producers to deliver features in an agile, iterative model.

• Perform code reviews and mentor engineers on modern patterns, including the use of AI for tests and documentation.

Qualifications:

• 6+ years of experience building web projects using modern development practices, including frontend UI and backend microservices

• Hands-on experience building products with AI capabilities, such as prompt engineering, RAG, or agentic workflows

• Experience building backend services using Node, Kotlin, Go, or similar technologies

• Experience with TypeScript, including modern patterns such as React hooks, functional components, and advanced type systems

• Experience deploying services on cloud-based infrastructures such as Kubernetes, AWS, GCP, or Azure

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Designing and building backend services in C#/.NET on Azure (AKS, Functions, Cosmos DB, SQL). Driving a large-scale infrastructure migrations. Full-stack feature delivery across APIs and frontends , UIs, APIs, and tools for business-critical workflows. Live-site engineering , owning production health, incident response, and observability. Building new applications from scratch as the platform expands into new areas. Opportunities to work on AI-powered product features including Copilot experiences and LLM integrations as the platform evolves.

A tenured, tight-knit team of 9 engineers where retention speaks for itself , people stay because the work matters and the team is genuinely great. High-impact, high-autonomy work: you own features end-to-end from design through production. Clear path to Principal and beyond , significant opportunities for technical ownership and scope growth. The platform is evolving fast , you’ll shape what it becomes, not just maintain what exists.

Improves artificial intelligence tools and practices across the software development lifecycle. Partners with internal stakeholders to determine customer/user requirements for scenarios. Leads discussions for architecture of complex products ensuring test strategies for solution quality. Mentors in identifying dependencies and producing extensible code across teams. Leads debugging efforts and application of coding patterns to improve code quality. Develops automation for production deployment targeting zero-touch when possible. Ensures visibility for compliance through audit trails and maintains understanding of regulations. Advocates new trends to adapt them to current problems and shares knowledge with peers. Supports collaboration with partner teams, ensuring proper integration before going live.

Responsible AI practices

Proactively takes responsibility for the content of their AI-generated requirements, design documents, code, and other assets, assisting other members of the team to do the same. Incorporates Responsible AI practices into the SDLC to ensure appropriate controls over AI-generated assets. Applies SDLC and engineering health measures (e.g., Accelerate, SPACE framework, Engineering System Success Playbook [ESSP]) to guide improvements to processes and practices, especially those involving AI. Experiments with AI tools and practices to improve their own capabilities, and provides recommendations on how to adopt them to other members of the team.

Coding

Leads by example across teams and mentors others to produce extensible, maintainable, well-tested, secure, and performant code used across products that adheres to design specifications. Leads efforts to continuously improve code performance, testability, maintainability, effectiveness, and cost, while learning about and accounting for relevant trade-offs. Identifies best practices and coding patterns and provides deep expertise in the coding and validation strategy. Creates and applies metrics to drive code quality and stability. Identifies and anticipates blockers or unknowns during the development process, escalates them, communicates how they will impact timelines, and then leads efforts to identify and implement strategies to address them. Leads efforts on using debugging tools, tests, logs, telemetry, and other methods, and proactively leads verification of assumptions while developing code before issues occur across products in production. Leverages minimal telemetry data, triangulates issues, and resolves with minimal iterations. Leads incident retrospectives to identify root causes of problems, the implementation of repair actions, and the identification of mechanisms to prevent incident recurrence. Reviews product code and test code to ensure it meets team standards, contains the correct test coverage, and is appropriate for the product or solution area.

Design

Owns and leads efforts and discussions for the architecture of aspects of complex products/solutions. Leads the testing and exploration of various design options across a set of complex product/solution scenarios, ensuring the strengths and weaknesses of each option are outlined and making recommendations for which design option is best. Creates proposals for architecture and design documents, and leads testing of hypotheses and proposed complex solutions. Leads the development of design documents that support user stories and other product requirements. Evaluates new technologies to solve classes of problems, and determines how to integrate these technologies within existing systems. Leads efforts to ensure system architecture and individual designs meet performance, scalability, resiliency, disaster recovery, and cost requirements. Mentors

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Designing and building backend services in C#/.NET on Azure (AKS, Functions, Cosmos DB, SQL) Driving a large-scale infrastructure migration from VMs to Kubernetes Full-stack feature delivery across GraphQL APIs and TypeScript frontends , UIs, APIs, and tools for business-critical workflows Live-site engineering , owning production health, incident response, and observability Building new applications from scratch as the platform expands into new areas Opportunities to work on AI-powered product features including Copilot experiences and LLM integrations as the platform evolves

A tenured, tight-knit team of 9 engineers where retention speaks for itself , people stay because the work matters and the team is genuinely great High-impact, high-autonomy work: you own features end-to-end from design through production Clear path to Principal and beyond , significant opportunities for technical ownership and scope growth The platform is evolving fast , you’ll shape what it becomes, not just maintain what exists

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Your responsibilities will include developing self-service security frameworks and 'paved roads' that allow engineering teams to ship secure code by default. You will focus on automated guardrails for common vulnerabilities, while prioritising deep-dive design reviews into complex business logic and data isolation issues. You will also partner with product and engineering teams to review designs early, contribute to threat modelling for new features and complex initiatives, and provide clear, actionable security guidance.

You will research emerging threats and evolving best practices, specifically regarding AI and LLM safety, and implement controls to secure these workflows. You will manage and evolve our approach to external penetration testing and bug bounties, driving remediation for findings and treating vulnerability management as an engineering problem.

You will contribute to the long-term roadmaps, metrics, and strategic planning for the security team. As a senior member of the team, you will lead complex threat modelling sessions for major product launches and define secure coding standards, and actively mentor other engineers to raise the technical security bar across the organisation.

We are looking for a highly experienced Product Security Engineer with a strong background in computer science or a related field, and proficiency in writing clean, maintainable code. You should have deep familiarity with JavaScript or TypeScript, Node.js, and modern web application frameworks, and be able to reason about the security implications of systems built on them. You should also have hands-on experience securing LLM integrations and identifying prompt injection or data leakage risks.

You will excel at communicating complex security risks to non-security stakeholders and enjoy collaborating cross-functionally to find solutions that balance security with engineering velocity. You will be comfortable working in a fast-paced environment, navigating ambiguity, continuously learning about emerging threats and technologies, and contributing to long-term security strategy.

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