Staff Backend Engineer: Real-Time Ads & Recommendations

Unity Technologies SF; Mountain View (CA); On-site; USD 178,000 - 261,000; Full time

Benefits offered by this job

Equity awards

Discretionary bonuses

Job summary

Unity Technologies SF is seeking a Staff Backend Engineer to lead Offer Delivery, setting the technical vision and architecture for real-time offer selection across bidding paths. You will own the backend services that decide which offers players see, ensuring scalability and reliability.

You will build Golang and Java services, collaborate with ML for ranking improvements, and mentor engineers while coordinating across auction, ML, platform, and product teams.

Qualifications

• Have owned a significant backend system and led architectural decisions.
• Experience designing large-scale, latency-sensitive services with complex logic.
• Strong backend proficiency in Go or Java; familiarity with gRPC.
• Able to implement observability, metrics, and tracing across services.
• Proven ability to drive technical work across teams and mentor engineers.

Responsibilities

• Architect and set the technical direction for Offer Delivery services.
• Build, test, and ship Go and Java services for real-time bidding and direct placement.
• Collaborate with ML to deploy ranking improvements and model serving integration.
• Lead across teams and align auction, ML, platform, and product groups.
• Ensure high availability and reliability with on-call rotations and monitoring.
• Mentor engineers and raise engineering standards.

Skills

Backend system ownership

Distributed systems

Go

Java

gRPC

Observability

Data streaming

Cross-team leadership

Tools

Go

Java

gRPC

Job description

Unity Technologies SF is seeking a Staff Backend Engineer to lead Offer Delivery, setting the technical vision and architecture for real-time offer selection across bidding paths. You will own the backend services that decide which offers players see, ensuring scalability and reliability.

You will build Golang and Java services, collaborate with ML for ranking improvements, and mentor engineers while coordinating across auction, ML, platform, and product teams.