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.
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.
Foundation (must-have software-engineering baseline)
- 3+ years of professional experience building production applications, with recent depth in AI/LLM-based or generative AI systems.
- Strong proficiency in at least one of Python, TypeScript, or JavaScript - Python expertise is required for our stack, including FastAPI, Pydantic, SQLAlchemy, or equivalent.
- Solid database skills across relational systems such as PostgreSQL and non-relational systems such as MongoDB or vector databases; familiar with caching and queues where applicable.
- Working knowledge of secure API design, authentication, authorization, and input validation.
- Comfortable with Git, GitLab CI/CD, and Docker/containers.
- Proven testing mindset and experience with automated test suites such as pytest.
Agent loop / harness engineering
- Demonstrated experience designing and operating agent loops in production - not just prompt-tuning a chatbot.
- Deep, practical understanding of prompting, context engineering, guardrails, context poisoning or pollution, and the parameters that govern model behavior.
- Hands-on experience integrating tools into agents through MCP, structured inputs/outputs, or sub-agent orchestration.
- Experience with an agent development framework such as LangChain, LangGraph, Claude Agent SDK, Pydantic AI, or comparable.
- Strong debugging instincts for non-deterministic systems and experience using practical logging, tracing, and evaluation techniques.
Creative AI
- Hands-on experience building generative image, video, 3D, or multimodal workflows.
- Experience with ComfyUI or a comparable workflow orchestration system.
- Familiarity with model families such as Stable Diffusion, FLUX, Qwen, or comparable open-source or hosted generative models.
- Experience with model customization or conditioning techniques such as LoRA, ControlNet, adapters, inpainting, pose, depth, reference images, or segmentation.
- Ability to assess generated content for quality, consistency, controllability, and production readiness.
- Experience integrating AI workflows with creative tools, DCC applications, game engines, or digital-content pipelines.
Agent memory
- Practical experience implementing memory for agents, including history compaction, context chaining, episodic memory, and short-term versus long-term separation.
- Familiarity with retrieval, retention, and context-reuse strategies for production applications.
Evaluation & quality
- Experience with test- and eval-driven development for LLM or generative AI systems, including building evaluation sets, regression suites, and automated quality checks.
- Experience incorporating user, artist, or production feedback into model and workflow iteration.
Communication
- English communication is a MUST - strong written and verbal English is required, and fluency is a significant plus given our globally distributed teams.
- Comfortable communicating technical and creative decisions and tradeoffs across cross-functional stakeholders.
Nice to have
- Experience running local LLMs or generative models using tools such as vLLM, Ollama, llama.cpp, PyTorch, ONNX, TensorRT, or comparable systems.
- Experience creating ComfyUI custom nodes, workflow APIs, or reusable generation pipelines.
- Familiarity with Blender, Maya, Houdini, Unreal Engine, Unity, Substance, Photoshop, or comparable creative tools.
- Experience training or fine-tuning generative models, LoRAs, adapters, or control models.
- Contributions to or familiarity with open-source agent harnesses or creative AI tools.
- Knowledge of game development, technical art, animation, texturing, cinematic production, or digital-content pipelines.
- Familiarity with licensing, provenance, and dataset considerations for generative media.