Full-Stack AI Engineer (Agentic Systems) – Shanghai, China | Visa + Salary Insights

📍 Location: Others

🏷 Type: Full-time

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Job Overview

This role at Thatgamecompany sits at the intersection of enterprise engineering, AI orchestration, and game-adjacent digital systems. The company is seeking a Full-Stack Engineer focused on building production-grade AI applications that improve internal workflows, automation, and cross-functional productivity. The ideal candidate is comfortable designing scalable backend systems, integrating LLM-driven agent frameworks, and collaborating across IT, publishing, legal, and infrastructure teams. This position is best suited for engineers with strong experience in TypeScript, Python, and modern AI ecosystems such as LangChain, RAG pipelines, and multi-agent orchestration tools.

📅 Job Timeline & Status

This role is positioned in an active hiring phase, likely within ongoing expansion of enterprise AI capabilities. Given the technical depth and cross-functional requirements, competition is expected to be high, especially from candidates with prior production-level AI systems experience. Applicants should treat this as an urgent opportunity, as enterprise AI roles in gaming studios typically move quickly once shortlisted pipelines are established.

🌍 Work Eligibility & Location

This is a fully Onsite role based in Shanghai. International applicants may be considered if they demonstrate strong production AI engineering experience and adaptability to cross-border collaboration. Familiarity with bilingual environments (English + Chinese) is a strong advantage.

💰 Salary Intelligence

Compensation is competitive for Shanghai-based AI engineering roles, especially those involving agentic systems, LLM orchestration, and enterprise-scale automation. Candidates with proven experience in production AI systems, cost optimization of LLM pipelines, and distributed system design can expect positioning at the upper end of the estimated range.

📊 Role Breakdown

This position centers around building and scaling enterprise AI systems that combine full-stack engineering with modern LLM orchestration. You will design and implement an internal agentic AI platform, enabling teams to deploy copilots, automation workflows, and intelligent assistants across business units. Core engineering work involves building APIs, frontend interfaces, and backend services using TypeScript and Python, while integrating frameworks like LangChain, LangGraph, and AutoGen.

A significant portion of the work involves constructing RAG pipelines (Retrieval-Augmented Generation), vector databases, and knowledge search systems optimized for latency and cost efficiency. Engineers will also manage LLM integration across providers such as OpenAI, Gemini, and Qwen, balancing token efficiency, caching strategies, and performance tuning. Approximately 40% of effort is expected in backend architecture, 30% in AI orchestration and prompt systems, and 30% in frontend and product integration layers. Strong emphasis is placed on scalability, governance, and secure AI deployment across enterprise environments.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a Senior-Level engineering role requiring deep expertise in both traditional full-stack systems and emerging AI orchestration stacks. The combination of enterprise AI governance, RAG pipelines, and multi-agent frameworks creates a high barrier to entry. Candidates without production LLM experience or system design capability may struggle to compete effectively.

🚀 Career Impact

This role provides strong long-term value due to its focus on enterprise AI infrastructure and agentic system design. Engineers gain exposure to cutting-edge orchestration frameworks and scalable AI deployment patterns that are directly transferable to high-growth AI companies, research labs, and platform engineering teams.

📋 Key Responsibilities

You will be responsible for building and maintaining enterprise-grade AI systems that enhance internal productivity and in-game operational workflows. Core duties include designing AI orchestration platforms, implementing agent-based automation systems, and integrating LLM APIs into production services. You will collaborate with cross-functional teams to identify high-impact AI use cases and transform them into scalable products. Responsibilities also include building secure and governed AI workflows, optimizing token usage, reducing inference costs, and maintaining system reliability. A strong focus is placed on integrating RAG systems, improving knowledge retrieval accuracy, and ensuring smooth user experience across AI-driven tools.

🎯 Application Strategy

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🧠 Fit & Positioning Analysis

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📅 Application Signals

Hiring momentum appears strong, with active enterprise AI expansion indicating ongoing candidate intake. Expect high competition due to the popularity of agentic AI roles in global markets. Response cycles are likely moderate, with shortlisted candidates contacted within a few weeks. Since no strict deadline is published, applications may close without notice, making early submission strategically important. Fast-moving AI teams typically prioritize candidates with immediate availability and demonstrable production-grade LLM systems experience.

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✅ Job Source & Verification

This listing is derived from an internal company posting context associated with Thatgamecompany. While no external publication timestamp is provided, verification is based on May 31, 2026 review alignment. Company career postings are generally reliable, though application timelines and availability may shift without formal public deadlines. Candidates should verify directly on the official careers portal for the most accurate and up-to-date hiring status.