Jobs in Mountain View, CA

About the role

Unity is hiring a Senior Software Engineer to build and operate the platform behind an internal AI product analytics agent, and the shared services other teams at Unity build on. This role will join the platform-facing half of the team. You will spend half of your time working on platform and infrastructure engineering: the backend services, APIs, integration surfaces, access control and operational foundations that make an internal AI product safe, fast and dependable at company scale. You will also support agent capability work; including orchestration, retrieval and the interfaces people use. The platform runs on GCP and serves data from BigQuery to users across Unity. Access control, reliability and cost are first-order product concerns, not afterthoughts. This role is one of two we're hiring on the team. If you'd rather spend your time in the analytics data layer, modelling datasets and improving the quality of what the agent knows, take a look at our Senior Software Engineer, Analytics Data & Applied AI role instead! This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

What you'll bring

• Experience designing, building and operating distributed systems, backend services or internal platforms in production.
• Strong backend and systems engineering skills: service design, API design, debugging and production operations.
• A solid grasp of distributed systems fundamentals, including scalability, reliability, fault tolerance and the trade-offs between them.
• Practical experience with cloud-native infrastructure
• Experience implementing authentication, authorisation or access control in systems handling sensitive data.
• Experience with, or a demonstrated interest in, LLM and agent systems, particularly orchestration and workflow design.
• A record of making progress on projects where the requirements are not fully defined.
• Experience building products for technical end users.
• Experience operating data-intensive platforms such as pipelines, streaming systems, storage layers or analytics infrastructure.
• Familiarity with privacy, security, compliance and cost management in large-scale platform environments.
• Experience applying AI or agentic tooling to engineering workflows.
• ideally GCP, plus container orchestration, CI/CD, infrastructure as code and observability tooling.

Benefits