DevOps & AI Engineer

What you’ll do

• Design and Build an AI-Powered Integration System: Architect, develop, and deploy a comprehensive AI-assisted platform that automates game project branch integration across Unreal Engine 5 and APEX. The system will support both Git and Perforce version control and integrate seamlessly with Jenkins-based CI/CD workflows.


• Develop Intelligent Conflict Resolution: Implement advanced LLM-powered agentic workflows to classify, triage, and resolve merge conflicts. Focus on deep contextual understanding, multi-pass investigation, and intelligent decision-making rather than relying on blind binary merges.


• Engine and Scripting Automation: Leverage native Python scripting and engine APIs to interact directly with Unreal Engine, automate tasks such as Blueprint recompilation and contract-change updates, and extend these capabilities to proprietary engines such as APEX.


• Full-Stack Development and Workflow Orchestration: Independently build both the backend agent framework and an internal, project-specific frontend dashboard. Design and manage complex state machines for "Paused Integration" workflows, enabling human-in-the-loop intervention and continuous learning through self-reflection mechanisms based on human resolutions.


• Define and Track Success Metrics: Establish, monitor, and refine key performance indicators (KPIs) that measure AI effectiveness, including Attempt Rate, Escalation Rate, and Rollback Rate, ensuring continuous improvement, operational efficiency, and system reliability.

• Version Control & CI/CD Mastery: Deep expertise in both Perforce and Git, with a strong understanding of their distinct workflows and underlying models, as well as hands-on experience designing and authoring Jenkins pipelines for robust CI/CD processes within mature development infrastructures.


• Game Engine & Asset Pipeline Knowledge: Working knowledge of Unreal Engine 5 project structures and asset pipelines, including a strong understanding of the challenges associated with merging game-specific assets such as .uasset files, Blueprints, and other engine-generated content.


• Applied AI/ML Practitioner: Proven ability to build practical applications using LLMs through APIs, including prompt engineering, context engineering, agentic frameworks, and retrieval-augmented generation (RAG). Experience applying these techniques to areas such as code-diff analysis, semantic understanding, and automated conflict resolution, with a focus on orchestration rather than model training.


• Polyglot Developer & Systems Integrator: Proficient in Python, C# for engine tooling, and C++, with full-stack web development experience (e.g., React and Node.js) for internal dashboard development. Skilled at orchestrating complex systems and integrations across multiple platforms and APIs, including version control systems, CI/CD tools, Jira, and Slack.


• Autonomous & Strategic Thinker: A highly self-directed professional capable of independently driving complex projects, strategically leveraging AI orchestration to delegate work to specialized agent sub-systems, and designing resilient architectures with robust state management.


• Game Industry Experience: Demonstrated experience in the game industry or engine development, with a strong appreciation for the unique technical and workflow complexities of game production.

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