Senior Full Stack Engineer, Big Viking Games

• This role is ideal for someone who is fluent in modern full stack development, understands how to work with AI coding tools and generative AI systems, and has the judgment to know where automation helps, where human review is required, and where quality cannot be compromised
• Several years of experience shipping production full stack web applications
• Strong TypeScript and Node.js experience
• Production experience with React, Next.js, or similar modern frontend frameworks
• Strong SQL and Postgres experience, including schema design, query performance, data integrity, and relational modeling
• Experience owning features or products end to end, not just working on one layer of the stack
• Strong product and engineering judgment, with the ability to identify when output is wrong, incomplete, fragile, or subtly off
• Experience turning ambiguous goals into clear specs, technical plans, and deliverable milestones
• Comfort working with content-generation systems, data pipelines, workflow orchestration, staged processing, approval flows, or similar production systems
• Strong understanding of APIs, backend services, frontend product surfaces, data models, and system boundaries
• Disciplined git, pull request, review, testing, and deployment practices
• Ability to work independently, make sound technical decisions, and own a complete area without heavy hand-holding
• Strong communication skills with both technical and non-technical stakeholders
• A practical mindset, high ownership, and the ability to move quickly without dropping the quality bar
• We are looking for someone who is not just curious about AI, but already understands how to use it productively. You should be able to demonstrate:
• AI coding agents and AI-assisted development workflows
• Generative AI systems that produce structured, reviewable outputs
• Prompting, spec-writing, workflow design, and model output review
• Building systems where AI accelerates work but humans remain in control of quality
• Evaluating generated outputs for correctness, consistency, usability, and production readiness
• Designing guardrails, review gates, retries, approval flows, and escalation paths
• Understanding where AI can safely automate work and where human judgment is still required
• The ideal candidate is a senior product-minded engineer who can build real systems from unclear starting points. They can think through the product experience, the data model, the workflow, the API, the user interface, and the quality controls required to make the system useful in production
• They are not simply using AI to write code faster. They understand how to direct AI, review its output, design better workflows around it, and turn AI-assisted processes into reliable products that teams can actually use
• They are comfortable moving fast, but they do not confuse speed with sloppiness. They care about clean architecture, strong product judgment, maintainable code, reliable workflows, and high-quality output
• This role is best suited for someone who wants ownership of a meaningful AI product area inside a live-service gaming company and is excited by the opportunity to help shape how game content, tools, and workflows are built in the future

Desirable

• Big Viking Games is hiring a Senior Full Stack Engineer to build AI-enabled products, workflows, tools, and systems that help turn creative direction into production-ready game content at scale
• This is a hands-on product engineering role for someone who can own a vertical end to end, from the data model and backend services to APIs, orchestration logic, human review workflows, and the user interface the team operates from
• You will not be working on a small slice of someone else’s codebase. You will be expected to take ambiguous goals, turn them into clear technical plans, build practical systems, and own the quality of the result
• You will build internal AI-enabled products, tools, systems, and workflows that help our teams create, review, approve, manage, and ship game content more efficiently. This may include:
• Tools that turn creative direction into structured production workflows
• AI-assisted content generation systems with human review and approval gates
• Internal products that help designers, artists, product managers, and live operations teams produce and manage content
• Data models, APIs, queues, orchestration layers, and UI surfaces that support repeatable workflows
• Agentic workflows that break complex production tasks into reliable, reviewable steps
• Systems that track inputs, generated outputs, approvals, revisions, quality checks, and production readiness
• Workflow automation that reduces manual work while keeping creative and quality standards high
• You will own the quality of what the system produces, not just the plumbing that moves data around
• Design, build, test, and maintain full stack applications that support AI-enabled game production workflows
• Own features end to end, including data modeling, backend logic, API design, frontend implementation, deployment, and ongoing improvement
• Build structured generation workflows that produce reliable, reviewable outputs from AI models
• Create human-in-the-loop review systems so teams can steer, approve, reject, edit, and improve generated content
• Translate ambiguous creative or operational goals into clear specifications, scoped plans, and production-ready systems
• Build internal tools that improve speed, consistency, visibility, and quality across content production workflows
• Partner with engineering, product, design, art, live operations, and leadership to understand workflow pain points and build practical solutions
• Implement approval steps, audit trails, retries, staged processing, idempotency, and other patterns required for reliable production systems
• Use AI coding agents and assistants as part of your daily workflow, while maintaining strong engineering judgment and code quality
• Review generated code, model outputs, workflow logic, and product behavior with a high bar for accuracy and usability
• Improve system reliability, observability, documentation, maintainability, and developer experience
• Contribute to a practical AI-first engineering culture focused on speed, quality, and measurable business impact