Senior AI Engineer

PLAY, GROW and WIN To be a part of Virtuos means to be a creator. At Virtuos, we harness the latest technologies to make games better and more immersive than ever before. That is why we pride ourselves in constantly pushing the boundaries of possibility since our founding in 2004. Virtuosi is a team of experts – people who have come together to share their mutual passion for making and playing games. People with the same enthusiasm for exploring new ideas and the constant drive to excel in their field. People who believe in earning success through dedication. At Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win – together. ABOUT THE POSITION We are looking for a Senior AI Engineer to help design and deliver agentic and generative AI systems that power R&D tooling for video game asset pipelines and production workflows. You will help shape the technical direction of our internal agent platform while building creative AI workflows that support artists, technical artists, and production teams. This is a senior, hands-on individual contributor role: you will write code, help design agentic architectures, build generative content pipelines, and partner with stakeholders across studios to turn emerging AI capabilities into production-grade tools. RESPONSIBILITIES Agent platform Design and build key parts of our internal agent libraries - the core abstractions and developer ergonomics that let teams across the company build agents quickly and consistently. Contribute to the architecture of our shared agent runtime and deployment patterns, helping teams run and maintain agents across production workflows. Help define and evolve the agent loop / harness: prompt orchestration, tool invocation, sub-agent delegation, and recovery behavior. Bring in reference patterns from the broader ecosystem, including open-source agent loops and harness projects, and adapt them to creative production use cases. Agent loop & harness engineering Drive prompting and context strategy at scale: system prompt design, guardrails, mitigation of context poisoning and pollution, and management of context windows and model parameters. Design tool interfaces for agents: MCP servers, structured inputs/outputs for context, and sub-agent composition patterns. Advocate for typed-agent frameworks, clear debugging patterns, and practical tracing for non-deterministic workflows. Evaluate and integrate hosted and local LLM options where latency, cost, quality, or data-residency requirements demand it. Creative AI workflows Design, build, and maintain generative workflows for 2D assets, video, textures, concepts, and 3D-related content. Evaluate and integrate image, video, multimodal, and 3D generation models for game-production use cases. Develop and optimize node-based generation workflows using tools such as ComfyUI or comparable systems. Customize generative models and workflows using techniques such as LoRA, ControlNet, adapters, inpainting, reference conditioning, depth, pose, or segmentation guidance. Build workflows that improve controllability, style consistency, editability, and downstream production readiness. Partner with artists and technical artists to translate creative requirements into repeatable AI-assisted workflows. Creative tool and pipeline integration Integrate agentic and generative AI systems with DCC tools and game-production environments such as Blender, Maya, Houdini, Unreal Engine, Unity, Substance, or comparable platforms. Build plugins, scripts, services, APIs, or MCP-based integrations that connect AI systems with asset and content pipelines. Connect generative workflows with asset-management, review, and publishing systems. Work with art and production teams to ensure generated outputs meet project, format, and engine-ingestion requirements. Agent memory Design and build the key parts of the memory layer used across our agents: conversation history management, context chaining, and episodic memory. Help define the boundary between short-term working context and long-term persistent memory. Develop practical strategies for history compaction, retrieval, retention, and context reuse across production workflows. Test- and eval-driven development Build practical evaluation workflows for agentic and generative systems, including regression tests, representative prompts, workflow traces, and quality benchmarks. Evaluate visual quality, prompt adherence, style consistency, temporal consistency, asset usability, and artist acceptance where applicable. Build harnesses and CI checks that let us iterate on prompts, models, tools, and generation workflows with confidence. Use measurable technical and production signals to guide improvements, including output acceptance, iteration speed, edit time, and workflow adoption. Backend & platform foundations Design and build scalable backend services and secure RESTful APIs in Python using FastAPI, with strong data modeling across relational and non-relational stores. Apply appropriate authentication, authorization, input validation, and robust error handling for agent- and workflow-facing endpoints. Implement caching, queues, retrieval systems, and vector storage where the workload requires it. Build and optimize model-serving and inference workflows for hosted and locally deployed models. Quality, delivery & collaboration Drive performance tuning, code reviews, and technical documentation within your area of the AI platform. Maintain CI/CD with Git/GitLab and Docker; ensure reproducible local-development and deployment pipelines. Partner with artists, technical artists, UI/UX, production, engineering, and game-team stakeholders to translate workflows into AI-powered solutions. Contribute to architectural decisions and share agentic- and creative-AI expertise with peers. Work within agile methodologies. QUALIFICATIONS Foundation (must-have software-engineering baseline) 3+ years of professi