About the role
Collaborate with data scientists, ML engineers, and product teams to define
requirements for agentic AI-driven bidding capabilities that observe, reason, and adapt autonomously. Architect and implement the next-generation agentic bidding platform, enabling AI agents to monitor marketplace signals, interpret advertiser and user behavior, and continuously optimize bidding strategies. Build large-scale data validation and quality frameworks to ensure correctness, consistency, and reliability across all auction-critical signals feeding the AI agents. Act as a Designated Responsible Individual (DRI): drive operational excellence, incident management, on-call readiness, and high-availability practices for mission-critical bidding services. Develop experimentation and simulation frameworks to validate agent behavior and optimize policies before deployment in live auctions. Proactively adopt new patterns, technologies, and engineering practices to improve availability, efficiency, performance, and scalability across the bidding stack. Set technical direction, mentor engineers, and foster a culture of high-quality execution, innovation, and accountability. Explore and invest in emerging AI techniques - multi-agent systems, adaptive optimization - to enhance the autonomy, intelligence, and impact of the bidding platform. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 4+ years of hands-on experience with large-scale streaming platforms such as Apache Spark or Flink. 4+ years of experience as a technical lead, including mentoring and guiding engineers. 7+ years of experience developing and deploying large-scale distributed systems in production environments. 7+ years of hands-on experience in machine learning operations (MLOps), including pipeline automation, monitoring, and lifecycle management. Domain knowledge and experience building large scale distributed bidding or auction platforms. Experience building real world applications using AI techniques. These
