24 days ago
Pune, IndiaStaff+
Responsibilities
- Architect, design, and build high-throughput, ultra-low-latency real-time bidding systems for buy-side advertising platforms.
- Lead development of bidder services handling millions of QPS using Golang, C, and C++.
- Design campaign pacing, budget management, and delivery optimization algorithms for CPA, ROAS, CTR, and CVR objectives.
- Own deal execution, auction participation, bid shading, and supply path optimization systems.
- Build real-time and near-real-time data pipelines for impressions, clicks, conversions, and attribution using Kafka, Flink, or Spark.
- Collaborate with ML engineers to productionize bid optimization, contextual bandit, reach forecasting, and incrementality models.
- Integrate and maintain OpenRTB, VAST, and CTV-specific programmatic advertising standards.
- Drive architecture decisions involving scalability, fault tolerance, data consistency, and latency optimization.
- Perform production profiling, latency tuning, and distributed-systems debugging.
- Mentor engineers, establish coding and design standards, and lead technical reviews.
- Evaluate technologies, auction strategies, and optimization frameworks.
Requirements
- At least eight years of software engineering experience with significant ad tech, performance advertising, or buy-side DSP bidder experience.
- Strong hands-on Golang experience building low-latency, high-scale backend systems.
- Proven experience designing and operating real-time bidding platforms, bidders, or ad-serving systems.
- Deep understanding of campaign pacing, budget allocation, and performance optimization algorithms.
- Experience with streaming and distributed systems such as Kafka, Flink, or Spark Streaming.
- Strong familiarity with OpenRTB, VAST, and programmatic advertising workflows.
- Knowledge of SQL, PostgreSQL, and large-scale analytics platforms such as Snowflake or BigQuery.
- Experience with AWS, GCP, or Azure and containerized environments using Docker and Kubernetes.
- Strong foundation in data structures, algorithms, and distributed-system design.
- Experience working cross-functionally with product, data science, analytics, and ML teams.
- Ability to own systems end-to-end, influence architecture, deliver at scale, drive technical direction, and mentor engineers.
- Bachelor’s degree in engineering, such as Computer Science or Information Technology, or an equivalent degree.
- Ability or willingness to use generative AI tools and IDEs such as GitHub Copilot, ChatGPT, Claude, Cursor, or Windsurf.
Benefits
- Hybrid schedule with three days in the office and two days working remotely.
- Paid leave programs and paid holidays.
- Healthcare, dental, vision, disability, and life insurance.
- Commuter benefits, physical and financial wellness programs, and unlimited DTO in the US.
- Mobile reimbursement, fully stocked pantries, and in-office catered lunches five days per week.
Tech Stack
Apache FlinkApache KafkaAWSAzureCC++DockerGoGoogle BigQueryGoogle Cloud PlatformKubernetesPostgreSQLSnowflakeSQL
Categories
