Senior Principal Software Engineer, Mobile App Monetization

About the Role:

Pub Matic is seeking an experienced and technically driven Principal Software Engineer to lead the design and development of our next-generation mobile app monetization platform . This role is focused on building high-performance, scalable, real-time systems that drive programmatic monetization across various mobile ad formats, including banners , interstitials , rewarded video , and native ads .

The ideal candidate is a seasoned backend engineer with deep domain expertise in mobile app advertising , OpenRTB protocols , and SDK-DSP-SSP integration workflows . You will work closely with Product, Data Science, and Monetization teams to design ML-integrated systems that optimize yield, latency, and reliability across our mobile ecosystem.

What You'll Do:

• Architect and implement scalable APIs and backend services powering mobile app monetization, including SDK-driven request handling, real-time targeting, ML-based decisioning, and campaign selection logic.
• Develop low-latency, high-throughput server-side systems capable of handling billions of RTB bid requests daily.
• Collaborate with ML Engineering and Data Science teams to integrate models for yield optimization and performance enhancement .
• Design and support A/B testing and experimentation frameworks to evaluate monetization strategies across diverse ad traffic.
• Contribute to the long-term technical strategy and roadmap for the mobile monetization platform.
• Champion engineering best practices in observability , fault tolerance , API performance , and modular architecture .

Who You Are:

• 8+ years of backend engineering experience , with a proven track record of building high-scale, low-latency systems , preferably in the mobile app advertising or programmatic AdTech domain.
• Strong programming expertise in C++ , with additional experience in Go or Java . Solid understanding of Linux/UNIX environments and system-level programming (multi-threading, multi-processing, memory management).
• Proficient in data structures, algorithms , and core computer science principles , with experience designing modular, scalable, and fault-tolerant systems .
• Deep understanding of programmatic advertising workflows , including RTB , OpenRTB 2.x/2.6 , bid lifecycle , and mobile SDK monetization .
• Experience integrating with DSPs, ad exchanges, mediation platforms , and working with SDK-DSP-SSP pipelines , including device graph utilization and session-aware ad serving .
• Familiarity with rewarded video , native ad formats , in-app gaming monetization , and mobile-specific privacy regulations (e.g., ATT , COPPA ).
• Hands-on experience with real-time ML inference pipelines , working closely with ML engineers and integrating model predictions into latency-sensitive systems.
• Practical knowledge of containerized and microservice architectures , with experience in API integrations , caching solutions , data stores , and cloud-native deployments .
• Skilled in troubleshooting production issues , performing root cause analysis, and supporting live systems with minimal downtime.
• Ability to write clean, modular, loosely coupled code and develop systems with strong observability and monitoring.
• Exposure to generative AI tools and familiarity with prompt engineering and AI-powered developer environments .
• Working knowledge of scripting languages such as Python , Shell , or Perl , and hands-on experience with relational databases, preferably MySQL .
• Excellent interpersonal, written, and verbal communication skills with a collaborative mindset and strong ownership over deliverables.
• Proficiency in AI-assisted coding, automation, prompt engineering, and an understanding of the strengths and limitations of LLM-generated code is a strong plus.

Bonus Qualifications:

• Hands-on experience with mobile monetization SDKs , including client-server interaction and mediation logic.
• Contributions to open-source AdTech projects , such as Prebid Mobile, RTBkit, or header bidding libraries.
• Familiarity with industry-standard ML model serving infrastructures designed for real-time inferencing.
• Understanding of mobile-specific user acquisition and…