Staff Software Engineer, Demand Bidder, Ad Serving Platform (Karnataka)

About the Team Rokus 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 Were 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 current 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. 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 re looking for curious, adaptable builders who can show how they ve used AI or automation to move faster, raise the bar, and scale their impact. We re value your AI skills if you have built fluency across the agentic engineering toolchain coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools. You know how to drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you. What Youll 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 distributed, 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 Were 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 youd rather get to the right answer than be the one whos right, and you take critical feedback in stride rather than personally - Genuinely collaborative and team-oriented, with an open mind toward other peoples approaches and the outgoing energy to work well across teams - Youve used AI coding assistants (e.g., Claude Code, Cursor, or similar) in real production work to accelerate design, implement, debug, and understand unfamiliar codebases - Youre curious about applying AI whether that means using AI to monitor system health .