{"id":3457059,"url":"https://alion.io/job/volmigames-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":4485770,"name":"Volmi Games","domain":"volmigames.com","url":"https://alion.io/company/volmigames","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":30,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Shanghai, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":38000,"max_usd":99000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":18},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Blender","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"ComfyUI","optional":false},{"name":"Context Engineering","optional":false},{"name":"ControlNet","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Git","optional":false},{"name":"GitLab","optional":false},{"name":"Houdini","optional":false},{"name":"JavaScript","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Maya","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OpenAI Agents SDK","optional":false},{"name":"Pydantic","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Qwen","optional":false},{"name":"Rest API","optional":false},{"name":"Stable Diffusion","optional":false},{"name":"TypeScript","optional":false},{"name":"Unity","optional":false},{"name":"Unreal Engine","optional":false},{"name":"Adobe Photoshop","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GitLab CI","optional":true},{"name":"llama.cpp","optional":true},{"name":"Ollama","optional":true},{"name":"ONNX","optional":true},{"name":"PEFT","optional":true},{"name":"PostgreSQL","optional":true},{"name":"PyTorch","optional":true},{"name":"SQLAlchemy","optional":true},{"name":"TensorRT","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-09-02T02:22:57Z","employer_posted_date":"2026-09-02","last_verified_at":"2026-10-31T21:06:09Z","board_verified":true,"closed_at":null,"days_open":59,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":59},"description":"PLAY, GROW and WIN\nTo be a part of Virtuos means to be a creator.\nAt 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.\nVirtuosi 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.\nAt Virtuos, we are at the forefront of gaming, creating exciting new experiences daily. Join us to Play, Grow and Win - together.\nABOUT THE POSITION\nWe 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.\nThis 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.\n Agent platform\nDesign 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.\nContribute to the architecture of our shared agent runtime and deployment patterns, helping teams run and maintain agents across production workflows.\nHelp define and evolve the agent loop / harness: prompt orchestration, tool invocation, sub-agent delegation, and recovery behavior.\nBring in reference patterns from the broader ecosystem, including open-source agent loops and harness projects, and adapt them to creative production use cases.\nAgent loop & harness engineering\nDrive prompting and context strategy at scale: system prompt design, guardrails, mitigation of context poisoning and pollution, and management of context windows and model parameters.\nDesign tool interfaces for agents: MCP servers, structured inputs/outputs for context, and sub-agent composition patterns.\nAdvocate for typed-agent frameworks, clear debugging patterns, and practical tracing for non-deterministic workflows.\nEvaluate and integrate hosted and local LLM options where latency, cost, quality, or data-residency requirements demand it.\nCreative AI workflows\nDesign, build, and maintain generative workflows for 2D assets, video, textures, concepts, and 3D-related content.\nEvaluate and integrate image, video, multimodal, and 3D generation models for game-production use cases.\nDevelop and optimize node-based generation workflows using tools such as ComfyUI or comparable systems.\nCustomize generative models and workflows using techniques such as LoRA, ControlNet, adapters, inpainting, reference conditioning, depth, pose, or segmentation guidance.\nBuild workflows that improve controllability, style consistency, editability, and downstream production readiness.\nPartner with artists and technical artists to translate creative requirements into repeatable AI-assisted workflows.\nCreative tool and pipeline integration\nIntegrate agentic and generative AI systems with DCC tools and game-production environments such as Blender, Maya, Houdini, Unreal Engine, Unity, Substance, or comparable platforms.\nBuild plugins, scripts, services, APIs, or MCP-based integrations that connect AI systems with asset and content pipelines.\nConnect generative workflows with asset-management, review, and publishing systems.\nWork with art and production teams to ensure generated outputs meet project, format, and engine-ingestion requirements.\nAgent memory\nDesign and build the key parts of the memory layer used across our agents: conversation history management, context chaining, and episodic memory.\nHelp define the boundary between short-term working context and long-term persistent memory.\nDevelop practical strategies for history compaction, retrieval, retention, and context reuse across production workflows.\nTest- and eval-driven development\nBuild practical evaluation workflows for agentic and generative systems, including regression tests, representative prompts, workflow traces, and quality benchmarks.\nEvaluate visual quality, prompt adherence, style consistency, temporal consistency, asset usability, and artist acceptance where applicable.\nBuild harnesses and CI checks that let us iterate on prompts, models, tools, and generation workflows with confidence.\nUse measurable technical and production signals to guide improvements, including output acceptance, iteration speed, edit time, and workflow adoption.\nBackend & platform foundations\nDesign and build scalable backend services and secure RESTful APIs in Python using FastAPI, with strong data modeling across relational and non-relational stores.\nApply appropriate authentication, authorization, input validation, and robust error handling for agent- and workflow-facing endpoints.\nImplement caching, queues, retrieval systems, and vector storage where the workload requires it.\nBuild and optimize model-serving and inference workflows for hosted and locally deployed models.\nQuality, delivery & collaboration\nDrive performance tuning, code reviews, and technical documentation within your area of the AI platform.\nMaintain CI/CD with Git/GitLab and Docker; ensure reproducible local-development and deployment pipelines.\nPartner with artists, technical artists, UI/UX, production, engineering, and game-team stakeholders to translate workflows into AI-powered solutions.\nContribute to architectural decisions and share agentic- and creative-AI expertise with peers.\nWork within agile methodologies.\n Foundation (must-have software-engineering baseline)\n3+ years of professional experience building production applications, with recent depth in AI/LLM-based or generative AI systems.\nStrong proficiency in at least one of Python, TypeScript, or JavaScript - Python expertise is required for our stack, including FastAPI, Pydantic, SQLAlchemy, or equivalent.\nSolid 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.\nWorking knowledge of secure API design, authentication, authorization, and input validation.\nComfortable with Git, GitLab CI/CD, and Docker/containers.\nProven testing mindset and experience with automated test suites such as pytest.\nAgent loop / harness engineering\nDemonstrated experience designing and operating agent loops in production - not just prompt-tuning a chatbot.\nDeep, practical understanding of prompting, context engineering, guardrails, context poisoning or pollution, and the parameters that govern model behavior.\nHands-on experience integrating tools into agents through MCP, structured inputs/outputs, or sub-agent orchestration.\nExperience with an agent development framework such as LangChain, LangGraph, Claude Agent SDK, Pydantic AI, or comparable.\nStrong debugging instincts for non-deterministic systems and experience using practical logging, tracing, and evaluation techniques.\nCreative AI\nHands-on experience building generative image, video, 3D, or multimodal workflows.\nExperience with ComfyUI or a comparable workflow orchestration system.\nFamiliarity with model families such as Stable Diffusion, FLUX, Qwen, or comparable open-source or hosted generative models.\nExperience with model customization or conditioning techniques such as LoRA, ControlNet, adapters, inpainting, pose, depth, reference images, or segmentation.\nAbility to assess generated content for quality, consistency, controllability, and production readiness.\nExperience integrating AI workflows with creative tools, DCC applications, game engines, or digital-content pipelines.\nAgent memory\nPractical experience implementing memory for agents, including history compaction, context chaining, episodic memory, and short-term versus long-term separation.\nFamiliarity with retrieval, retention, and context-reuse strategies for production applications.\nEvaluation & quality\nExperience with test- and eval-driven development for LLM or generative AI systems, including building evaluation sets, regression suites, and automated quality checks.\nExperience incorporating user, artist, or production feedback into model and workflow iteration.\nCommunication\nEnglish communication is a MUST - strong written and verbal English is required, and fluency is a significant plus given our globally distributed teams.\nComfortable communicating technical and creative decisions and tradeoffs across cross-functional stakeholders.\nNice to have\nExperience running local LLMs or generative models using tools such as vLLM, Ollama, llama.cpp, PyTorch, ONNX, TensorRT, or comparable systems.\nExperience creating ComfyUI custom nodes, workflow APIs, or reusable generation pipelines.\nFamiliarity with Blender, Maya, Houdini, Unreal Engine, Unity, Substance, Photoshop, or comparable creative tools.\nExperience training or fine-tuning generative models, LoRAs, adapters, or control models.\nContributions to or familiarity with open-source agent harnesses or creative AI tools.\nKnowledge of game development, technical art, animation, texturing, cinematic production, or digital-content pipelines.\nFamiliarity with licensing, provenance, and dataset considerations for generative 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