Senior Software Engineer, AI Authoring

Unity Technologies•Mountain View, CA

3d•$165,600 - $273,400

About The Position

Three billion people a month play something built in Unity. We're the team changing how those things get made — building AI that generates assets, writes and repairs code, and turns an idea into something playable faster than has ever been possible. Our group owns the backend and operations behind all of it: the cloud infrastructure our AI products run on, the data and experimentation platforms that tell us what works, the evaluation systems that tell us whether the AI is actually any good, and the operations that keep everything running across regions and customers. We're looking for a Senior Software Engineer who is genuinely AI-native: for whom agents and AI tooling are how the work gets done rather than a productivity add-on, and who can take a problem nobody has framed yet, explore it independently, and move quickly to something real. We've built the foundations over the past few months — CI/CD, infrastructure-as-code, deployment standards — and they work. The platform is stable, and we intend to keep it that way. What we have not solved is how much of understanding it still depends on people: when a metric moves, someone works out what it means; when something degrades, a human reads dashboards and makes the call; when a model changes, we find out more slowly than we should. None of that scales with the speed we're now shipping at, and none of it needs to stay manual. If you like problems where the answer isn't in a runbook yet, several of these are genuinely open.

Requirements

Hands-on, current use of AI and agent tooling in your own engineering work. Genuine daily practice, not familiarity with the concepts — and ideally experience pointing agents at problems beyond code generation. Expect to talk about what you have actually built
A track record of working independently on problems that weren't fully defined — choosing the direction, moving quickly to something real, and knowing when to change course
Experience building and shipping complex, user-facing software products at scale
Depth in observability — monitoring, logging, alerting and debugging with tools such as Grafana — and a point of view on making telemetry interpretable rather than merely present
An automation instinct in operational work — you have replaced a manual judgment step in production with a system that makes it for you, or cut the human effort in a detection-to-resolution loop
Hands-on experience with Microsoft Azure or Google Cloud Platform
Backend service development, including API design, and comfort working in an established CI/CD and infrastructure-as-code environment
Ability to translate business and user needs into technical solutions
Strong communication and interpersonal skills, with a proven ability to align stakeholders across disciplines and organizations

Nice To Haves

Experience building evaluation infrastructure for AI systems — benchmark harnesses, LLM-as-judge pipelines, or measuring model output quality at scale
Experience with the economics of agentic systems — inference and token cost, model routing, context and memory management, or checkpointing and state recovery for long-running agent work
Background in games, live-service operations, or player analytics

Responsibilities

Raise the ceiling on AI-native development. We use AI across our workflow today, and we're not satisfied with how far it goes. You'll push it considerably further — agentic code review and repair, generated tests that stay honest as requirements change, and tooling the team adopts because it makes the work faster. We want someone who will change how this team builds software, not someone who will use the tools we already have.
Rebuild observability so it explains itself. Our telemetry has gaps, and much of what we collect is ambiguous, unlabelled, or only meaningful to whoever built it. You'll define what we measure across system health and business outcomes, make each metric self-explanatory, and replace manual review and manual reaction with automated interpretation.
Make diagnosis agentic. Build the troubleshooting layer that correlates signals, proposes root causes, and takes safe automated action — so that understanding a production issue doesn't start with a person reading graphs.
Mature our evaluation infrastructure with our Quality Engineering Lead. Our products generate code, find and fix bugs, and produce art and design — output with no single correct answer. We have the beginnings of an evaluation system, and it isn't mature yet. You'd own the infrastructure side — making evaluation fast, repeatable and cheap enough to run continuously — partnering closely with the Quality Engineering Lead who owns the methodology.
Explore what AI can do for gaming LiveOps. Live games are managed continuously after launch: events and content, player behaviour and retention analysis, monetization, live health. We think Unity's data puts us in an unusual position to make that faster, smarter and far less manual. We are early here and genuinely do not know yet what it becomes — this is a problem to shape, not a roadmap to execute.
Make agentic systems affordable. As more of our product and our own workflow runs on inference, the economics become an engineering problem — token efficiency, routing work to the cheapest model that can do it, managing what an agent has to keep in context, and recovering agent state so a failed run resumes instead of starting over. You'll drive how we measure and optimize all of it.
Contribute to technical strategy and architecture for Unity AI and our backend platforms, run technical spikes with developers on Microsoft Azure and Google Cloud, and partner with product, design and other engineering teams to influence the roadmap.