About Big Viking Games Big Viking Games exists to make fans. We are a profitable, independent Canadian gaming company focused on building, operating, and growing long-standing online game communities. These are enduring live-service virtual worlds with rich in-game economies, virtual goods, deep social interaction, and player communities measured in years, not sessions.

We are now rebuilding the company as an AI-first studio. AI agents are already changing how we build, test, review, produce, and operate. We believe a small team of exceptional builders, amplified by well-architected AI systems, can outperform teams many times larger.

This role exists to help prove that, operationalize it, and define what the next generation of game development looks like.

Big Viking

Games is hiring a Principal Engineer, Agentic Products & Workflows to build the systems that make an AI-first game studio real. This is a founding-level engineering seat at the center of our AI transformation. You will help architect and build the agentic platform, autonomous engineering workflows, AI-enabled content pipelines, review systems, integration layers, and observability infrastructure that allow agents to produce reliable, reviewable, production-grade output for live games.

This is not a role for someone who is simply curious about AI. You should already be building with agents, shipping systems, testing workflows, using AI coding tools daily, and developing opinions from real production experience. We care less about pedigree and more about what you have built, how you think, and whether your systems survive contact with real users, real content, real revenue, and real production constraints.

You will own verticals end to end: architecture, orchestration, data models, backend services, APIs, evaluation loops, human review surfaces, observability, quality controls, and the production workflows teams use every day. Agentic systems are nondeterministic, tool-driven, context-dependent, and often operating with minimal supervision.

Autonomous Engineering Platform

Autonomous engineering workflows that can take a scoped ticket toward a reviewed, tested pull request AI-to-AI review layers where agents critique, test, validate, and gate each other's output before a human needs to intervene Prediction and confidence systems that help agents know when to proceed, when to ask, and when to stop Evaluation infrastructure, test harnesses, traces, metrics, and dashboards that catch hallucinations, regressions, grounding gaps, quality drift, and cost spikes before they reach production Integration layers that connect agents safely to codebases, tickets, repositories, data sources, tools, documentation, and production workflows LiveOps Content Pipelines The AI-enabled production systems that turn creative direction into production-ready game content at scale. Content generation workflows that produce structured, reviewable output aligned to YoWorld, FishWorld, and our quality standards Human review surfaces where designers, artists, product managers, and live operations teams can steer, approve, reject, revise,



and improve generated content Prompt and spec composition systems that make quality repeatable rather than dependent on individual heroics Tooling that helps creative and production teams move faster without lowering the bar Integration layers that move approved content safely into live game workflows You will own the quality of what these systems produce, not just the plumbing that moves data around. Architect, build, test, and operate agentic systems that support AI-enabled game production, autonomous engineering, content workflows, and internal tools Own the agentic platform end to end, including orchestration primitives, workflow design, review loops, memory, evaluation, observability, and integration into live-game systems Build systems where agents can safely use tools, call APIs, interact with repositories, retrieve context, modify assets, generate structured outputs, and escalate when they should not proceed Design guardrails, validation layers, eval suites, review gates, approval flows, and recovery paths that keep autonomous output at production quality Ship against outcomes that matter: cost per asset, quality and rework rate, throughput, review speed, placement speed, escaped-defect rate, uptime, and production trust Translate ambiguous creative, operational, and engineering goals into clear specifications, scoped plans, and shipped systems Partner directly with creative AI, engineering, product, design, art, live operations, QA, and leadership to find the highest-leverage problems and solve them Set the engineering bar for agentic development at BVG through architecture, review standards, documentation, patterns, and mentorship Use AI coding agents as a core part of your daily workflow, directing them, reviewing their output, and building infrastructure that makes them more useful for everyone Help define a practical AI-first engineering culture focused on speed, quality, reliability, and measurable business impact Substantial experience shipping and operating production software at scale Strong full stack engineering depth, ideally with TypeScript, Node.js, React, Next.js, SQL, Postgres, APIs, backend services, queues, workers, and production web applications Real experience building agentic systems, autonomous workflows, AI-enabled products, or production AI infrastructure Daily, fluent use of AI coding agents such as Claude Code, Cursor, Codex, or similar tools as part of how you work Robust first-principles engineering judgment.

Experience with orchestration, tool use, task planning, state management, context management, retrieval, workflow reliability, and human review systems Experience building or operating evals, traces, guardrails, test harnesses, quality checks, or other systems that make AI output measurable and trustworthy Strong product judgment and the ability to identify when generated output is wrong, incomplete, fragile, off-brand, unsafe, or subtly low quality Disciplined git, pull request, code review, testing, deployment, and production operations practices, whether the author is human or agent Ability to mentor other engineers,



set patterns, and raise the technical bar around you AI and Agentic Systems Experience Agentic systems you have designed, built, shipped, or operated Practical fluency with AI coding agents and multi-agent workflows Understanding of model behavior, including context windows, retrieval failure modes, grounding gaps, hallucination patterns, calibration, prompt design, and spec design Experience with eval suites, regression tests, quality measurement, observability, and production monitoring for AI systems Clear judgment about where AI can automate work, where human review is required, and where quality cannot be compromised Systems that run when you are away from the keyboard and the instrumentation to trust them Experience shipping generative AI or agentic AI features in customer-facing or business-critical production environments Experience with MCP, OpenAI, Anthropic, Gemini, Vercel AI SDK, LangGraph, LlamaIndex, LangChain, or similar AI development ecosystems Experience building internal tools for creative production, game operations, content pipelines, asset generation, QA automation, or media workflows Experience with art, animation, asset pipelines, Flash, Animate, or creative tooling Strong visual judgment and the ability to push generated content toward better quality, consistency, and production value Experience in gaming, live-service products, virtual worlds, social games, free-to-play games, high-DAU consumer products, or other production environments where reliability and quality matter every day Zero-to-one, founding-engineer, or early-stage platform-building experience They are not using AI simply to write code faster. They are architecting the systems that AI runs inside: orchestration, tools, memory, evals, review loops, observability, calibration, recovery, and human control surfaces. They can think through the product experience, the data model, the workflow, the orchestration pattern, the interface, the failure modes, the quality controls, and the production risks, then go build the system.

They turn AI demos into production infrastructure. This role is best suited for someone who wants founding-level ownership of a meaningful AI platform inside a profitable live-service gaming company, and who is excited to help define how game content, engineering workflows, and autonomous systems are built for the next decade. The expected base salary range for this role is CAD $175,000 to $200,000, depending on experience, technical depth, demonstrated agentic systems experience, and overall fit.

Group Retirement Savings

Plan matching and participation ~ Comprehensive benefits package, including health, dental, and vision coverage ~ Health and Wellness spending account ~15 vacation days ~A founding-level seat on the systems that will define how an AI-first game studio operates ~ Exposure to live-service games, content production, game operations, internal platform development, and autonomous engineering workflows ~ A high-ownership role with meaningful influence over how AI is adopted across the company ~ A leadership team that is all-in on practical AI adoption, not performative AI theatre Big Viking Games is committed to creating an inclusive and accessible environment for all candidates.

📌 Principal Engineer, Agentic Products & Workflows (Toronto)
🏢 Big Viking Games
📍 Toronto