Staff Software Engineer, Demand Bidder, Ad Serving Platform

About the Team

Roku's Ad Serving Team builds and operates the real-time advertising platform that powers all of Roku’s ad monetization across video, display, and native ad formats. Within Ad Serving, the Demand Bidder team owns the high throughput and low latency systems responsible for serving relevant ads for tens of thousands of campaigns through targeting, scoring, bidding, auctions, measurement and more. Every millisecond and every decision carries direct, measurable revenue impact, and the team operates with the high engineering rigor that this demands.

About the Role

We're hiring a Senior Software Engineer (Staff scope) to help scale and evolve this platform. Demand Bidder is a large, high-throughput system driving our next phase of growth. As we onboard a rapid wave of new businesses, we are actively scaling and advancing our architecture — including state of the art pacing engine, scoring/ML engine, modularizing designed for agentic development. Our reliability bar keeps climbing alongside our business scale. We need someone who can rapidly master this intricate ecosystem and take immediate ownership of key initiatives.

For California Only — The estimated annual salary for this position is between $195,000 – $408,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

How will I use AI at Roku? 

At Roku, we don’t just use AI, we work with it. AI agents and smart tools help power drafts, analysis, and repetitive workflows, while our people bring direction, judgment, and accountability.  
We value curious, adaptable builders, who can show how they’ve used AI, agents, or automation to move faster, improve quality, and scale their impact. Strong candidates know how to frame problems, guide AI-assisted work, check the output, and learn quickly. Above all, they bring curiosity, adaptability, and sound judgment. 

What You'll Be Doing

• Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements
• Take end-to-end ownership of specific subsystems: architecture, implementation, testing, deployment, on-call, and long-term evolution
• Build a working mental model of a highly distributes, complex production system, and make high-leverage contributions
• Identify opportunities to continuously evolve the system and tooling
• Partner with engineers and applied scientists working at the intersection of distributed systems and statistical/ML-driven decision-making
• Diagnose and resolve subtle, often timing- or statistics-related issues in a highly concurrent, multi-region distributed system
• Mentor other engineers and raise the bar on engineering rigor, testing discipline, and operational excellence across the team
• Communicate clearly with both technical and non-technical stakeholders, and drive alignment across engineering, product, and business partners
  
  

We're Excited If You Have

• 10+ years of experience designing, building, and operating large-scale, low-latency distributed systems — ideally including at least one system you built substantially from the ground up
• A demonstrated track record of owning complex systems end-to-end: design, build, operate, on-call, and iterate based on production feedback
• Proven ability to ramp quickly into unfamiliar, complex, large codebases and become productive fast — you enjoy the “figure it out” part of the job as much as the “build it” part
• Experience evolving and refactoring live, business-critical systems without compromising uptime or correctness
• Strong command of Java, with a solid foundation in algorithms, data structures, concurrency/multi-threading, and performance optimization
• Practical experience with distributed caching, high-throughput messaging/streaming systems, and SQL/NoSQL datastores
• Comfort operating in cloud infrastructure (GCP or AWS) at scale
• Exposure to applying statistical, control-theory, or ML-driven techniques within production decision-making systems is a strong plus
• Real-time bidding / ad-tech domain experience is a big plus, but deep experience in adjacent high-stakes, low-latency domains (trading systems, large-scale ranking/recommendation, matchmaking, risk/fraud systems) is equally valued
• B.S. or M.S. in Computer Science, Engineering, or equivalent practical experience
• High ownership, self-motivation, critical thinking, and comfort operating with ambiguity
• Low-ego and nonpolitical — you'd rather get to the right answer than be the one who's right, and you take critical feedback in stride rather than personally
• Genuinely collaborative and team-oriented, with an open mind toward other people's approaches and the outgoing energy to work well across teams
• You've used AI coding assistants (e.g., Claude Code, Cursor, or similar) in real production work to accelerate design, implement, debug, and understand unfamiliar codebases. You have informed opinions on how best to leverage
• You're curious about applying AI – whether that mean using AI to monitor system health, triage issues or develop agentic workflows
• You hold yourself to a high bar of correctness and understanding of what you ship, even as these tools accelerate your pace
• Deep prior experience isn't required — genuine curiosity and a willingness to help shape how the team uses these tools responsibly is what matters most
  
  

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